Language：English   Publishing type：Research paper (scientific journal)   Publisher：IOS Press  

BACKGROUND: Imaging examinations are crucial for diagnosing acute ischemic stroke, and knowledge of a patient’s body weight is necessary for safe examination. To perform examinations safely and rapidly, estimating body weight using head computed tomography (CT) scout images can be useful. OBJECTIVE: This study aims to develop a new method for estimating body weight using head CT scout images for contrast-enhanced CT examinations in patients with acute ischemic stroke. METHODS: This study investigates three weight estimation techniques. The first utilizes total pixel values from head CT scout images. The second one employs the Xception model, which was trained using 216 images with leave-one-out cross-validation. The third one is an average of the first two estimates. Our primary focus is the weight estimated from this third new method. RESULTS: The third new method, an average of the first two weight estimation methods, demonstrates moderate accuracy with a 95% confidence interval of ±14.7 kg. The first method, using only total pixel values, has a wider interval of ±20.6 kg, while the second method, a deep learning approach, results in a 95% interval of ±16.3 kg. CONCLUSIONS: The presented new method is a potentially valuable support tool for medical staff, such as doctors and nurses, in estimating weight during emergency examinations for patients with acute conditions such as stroke when obtaining accurate weight measurements is not easily feasible.

DOI： 10.3233/xst-230087

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Publishing type：Research paper (scientific journal)   Publisher：Springer Science and Business Media LLC  

Abstract

This study proposes a deep convolutional neural network (DCNN) classification for the quality control and validation of breast positioning criteria in mammography. A total of 1631 mediolateral oblique mammographic views were collected from an open database. We designed two main steps for mammographic verification: automated detection of the positioning part and classification of three scales that determine the positioning quality using DCNNs. After acquiring labeled mammograms with three scales visually evaluated based on guidelines, the first step was automatically detecting the region of interest of the subject part by image processing. The next step was classifying mammographic positioning accuracy into three scales using four representative DCNNs. The experimental results showed that the DCNN model achieved the best positioning classification accuracy of 0.7836 using VGG16 in the inframammary fold and a classification accuracy of 0.7278 using Xception in the nipple profile. Furthermore, using the softmax function, the breast positioning criteria could be evaluated quantitatively by presenting the predicted value, which is the probability of determining positioning accuracy. The proposed method can be quantitatively evaluated without the need for an individual qualitative evaluation and has the potential to improve the quality control and validation of breast positioning criteria in mammography.

DOI： 10.1038/s41598-023-34380-9

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Other Link： https://www.nature.com/articles/s41598-023-34380-9

Language：English   Publishing type：Research paper (scientific journal)  

This study aimed to determine the optimal radiographic conditions for detecting lesions on digital chest radiographs using an indirect conversion flat-panel detector with a copper (Cu) filter. First, we calculated the effective detective quantum efficiency (DQE) by considering clinical conditions to evaluate the image quality. We then measured the segmentation accuracy using a U-net convolutional network to verify the effectiveness of the Cu filter. We obtained images of simulated lung tumors using 10-mm acrylic spheres positioned at the right lung apex and left middle lung of an adult chest phantom. The Dice coefficient was calculated as the similarity between the output and learning images to evaluate the accuracy of tumor area segmentation using U-net. Our results showed that effective DQE was higher in the following order up to the spatial frequency of 2 cycles/mm: 120 kV + no Cu, 120 kV + Cu 0.1 mm, and 120 kV + Cu 0.2 mm. The segmented region was similar to the true region for mass-area extraction in the left middle lobe. The lesion segmentation in the upper right lobe with 120 kV + no Cu and 120 kV + Cu 0.1 mm was less successful. However, adding a Cu filter yielded reproducible images with high Dice coefficients, regardless of the tumor location. We confirmed that adding a Cu filter decreases the X-ray absorption efficiency while improving the signal-to-noise ratio (SNR). Furthermore, artificial intelligence accurately segments low-contrast lesions.

DOI： 10.1007/s12194-023-00719-0

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Public Library of Science (PLoS)  

Background

Pulmonary thromboembolism is a serious disease that often occurs in disaster victims evacuated to shelters. Deep vein thrombosis is the most common reason for pulmonary thromboembolism, and early prevention is important. Medical technicians often perform ultrasonography as part of mobile medical screenings of disaster victims but reaching all isolated and scattered shelters is difficult. Therefore, deep vein thrombosis medical screening methods that can be easily performed by anyone are needed. The purpose of this study was to develop a method to automatically identify cross-sectional images suitable for deep vein thrombosis diagnosis so disaster victims can self-assess their risk of deep vein thrombosis.

Methods

Ultrasonographic images of the popliteal vein were acquired in 20 subjects using stationary and portable ultrasound diagnostic equipment. Images were obtained by frame split from video. Images were classified as “Satisfactory,” “Moderately satisfactory,” and “Unsatisfactory” according to the level of popliteal vein visualization. Fine-tuning and classification were performed using ResNet101, a deep learning model.

Results

Acquiring images with portable ultrasound diagnostic equipment resulted in a classification accuracy of 0.76 and an area under the receiver operating characteristic curve of 0.89. Acquiring images with stationary ultrasound diagnostic equipment resulted in a classification accuracy of 0.73 and an area under the receiver operating characteristic curve of 0.88.

Conclusion

A method for automatically identifying appropriate diagnostic cross-sectional ultrasonographic images of the popliteal vein was developed. This elemental technology is sufficiently accurate to automatically self-assess the risk of deep vein thrombosis by disaster victims.

DOI： 10.1371/journal.pone.0282747

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Language：Japanese   Publisher：(公社)日本放射線技術学会  

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Language：Japanese   Publishing type：Research paper (scientific journal)  

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Language：Japanese   Publishing type：Research paper (scientific journal)  

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Language：Japanese   Publishing type：Research paper (scientific journal)  

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Language：Japanese   Publishing type：Research paper (scientific journal)  

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Springer Science and Business Media LLC  

PURPOSE: Although surgery is the primary treatment for lung cancer, some patients experience recurrence at a certain rate. If postoperative recurrence can be predicted early before treatment is initiated, it may be possible to provide individualized treatment for patients. Thus, in this study, we propose a computer-aided diagnosis (CAD) system that predicts postoperative recurrence from computed tomography (CT) images acquired before surgery in patients with lung adenocarcinoma using a deep convolutional neural network (DCNN). METHODS: This retrospective study included 150 patients who underwent curative surgery for primary lung adenocarcinoma. To create original images, the tumor part was cropped from the preoperative contrast-enhanced CT images. The number of input images to the DCNN was increased to 3000 using data augmentation. We constructed a CAD system by transfer learning using a pretrained VGG19 model. Tenfold cross-validation was performed five times. Cases with an average identification rate of 0.5 or higher were determined to be a recurrence. RESULTS: The median duration of follow-up was 73.2 months. The results of the performance evaluation showed that the sensitivity, specificity, and accuracy of the proposed method were 0.75, 0.87, and 0.82, respectively. The area under the receiver operating characteristic curve was 0.86. CONCLUSION: We demonstrated the usefulness of DCNN in predicting postoperative recurrence of lung adenocarcinoma using preoperative CT images. Because our proposed method uses only CT images, we believe that it has the advantage of being able to assess postoperative recurrence on an individual patient basis, both preoperatively and noninvasively.

DOI： 10.1007/s11548-022-02694-0

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Other Link： https://link.springer.com/article/10.1007/s11548-022-02694-0/fulltext.html

Language：English   Publishing type：Research paper (scientific journal)   Publisher：Springer Science and Business Media LLC  

Abstract

Identification of individuals is performed when a corpse is found after a natural disaster, incident, or accident. DNA and dental records are frequently used as biometric fingerprints; however, identification may be difficult in some cases due to decomposition or damage to the corpse. The present study aimed to develop an individual identification method using thoracic vertebral features as a biological fingerprint. In this method, the shortest diameter in height, width, and depth of the thoracic vertebrae in the postmortem image and a control antemortem were recorded and a database was compiled using this information. The Euclidean distance or the modified Hausdorff distance was calculated as the distance between two points on the three-dimensional feature space of these measurement data. The thoracic vertebrae T1-12 were measured and the pair with the smallest distance was considered to be from the same person. The accuracy of this method for identifying individuals was evaluated by matching images of 82 cases from a total of 702 antemortem images and showed a hit ratio of 100%. Therefore, this method may be used to identify individuals with high accuracy.

DOI： 10.1038/s41598-022-20748-w

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Other Link： https://www.nature.com/articles/s41598-022-20748-w

Language：English   Publishing type：Research paper (scientific journal)   Publisher：Springer Science and Business Media LLC  

The convenience of imaging has improved with digitization; however, there has been no progress in the methods used to prevent human error. Therefore, radiographic incidents and accidents are not prevented. In Japan, image interpretation is conducted for incident prevention; nevertheless, in some cases, incidents are overlooked. Thus, assistance from a computer-aided quality assurance support system is important. This study developed a method to identify hand image direction, which is an elementary technology of a computer-aided quality assurance support system. In total, 14,236 hand X-ray images were used to classify hand directions (upward, downward, rightward, and leftward) commonly evaluated in clinical settings. The accuracy of the conventional classification method using original images, classification method with histogram equation images, and a novel classification method using binarization images for background removal via U-Net segmentation was evaluated. The following classification accuracy rates were achieved: 89.20% if the original image was input, 99.10% if the histogram equation image was input, and 99.70% if binarization images for background removal via U-Net segmentation was input. Our computer-aided quality assurance support system can be used to identify hand direction with high accuracy.

DOI： 10.1007/s12194-022-00675-1

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Other Link： https://link.springer.com/article/10.1007/s12194-022-00675-1/fulltext.html

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：SPIE  

DOI： 10.1117/12.2624139

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：IOP Publishing  

Abstract

This study investigates the equivalence or compatibility between U-Net and visual segmentations of fibroglandular tissue regions by mammography experts for calculating the breast density and mean glandular dose (MGD). A total of 703 mediolateral oblique-view mammograms were used for segmentation. Two region types were set as the ground truth (determined visually): (1) one type included only the region where fibroglandular tissue was identifiable (called the ‘dense region’); (2) the other type included the region where the fibroglandular tissue may have existed in the past, provided that apparent adipose-only parts, such as the retromammary space, are excluded (the ‘diffuse region’). U-Net was trained to segment the fibroglandular tissue region with an adaptive moment estimation optimiser, five-fold cross-validated with 400 training and 100 validation mammograms, and tested with 203 mammograms. The breast density and MGD were calculated using the van Engeland and Dance formulas, respectively, and compared between U-Net and the ground truth with the Dice similarity coefficient and Bland–Altman analysis. Dice similarity coefficients between U-Net and the ground truth were 0.895 and 0.939 for the dense and diffuse regions, respectively. In the Bland–Altman analysis, no proportional or fixed errors were discovered in either the dense or diffuse region for breast density, whereas a slight proportional error was discovered in both regions for the MGD (the slopes of the regression lines were −0.0299 and −0.0443 for the dense and diffuse regions, respectively). Consequently, the U-Net and ground truth were deemed equivalent (interchangeable) for breast density and compatible (interchangeable following four simple arithmetic operations) for MGD. U-Net-based segmentation of the fibroglandular tissue region was satisfactory for both regions, providing reliable segmentation for breast density and MGD calculations. U-Net will be useful in developing a reliable individualised screening-mammography programme, instead of relying on the visual judgement of mammography experts.

DOI： 10.1088/2057-1976/ac7ada

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Other Link： https://iopscience.iop.org/article/10.1088/2057-1976/ac7ada/pdf

Authorship：Corresponding author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：Springer Science and Business Media LLC  

Abstract

Background

Adolescent idiopathic scoliosis (AIS) is a three-dimensional spinal deformity that predominantly occurs in girls. While skeletal growth and maturation influence the development of AIS, accurate prediction of curve progression remains difficult because the prognosis for deformity differs among individuals. The purpose of this study is to develop a new diagnostic platform using a deep convolutional neural network (DCNN) that can predict the risk of scoliosis progression in patients with AIS.

Methods

Fifty-eight patients with AIS (49 females and 9 males; mean age: 12.5 ± 1.4 years) and a Cobb angle between 10 and 25 degrees (mean angle: 18.7 ± 4.5) were divided into two groups: those whose Cobb angle increased by more than 10 degrees within two years (progression group, 28 patients) and those whose Cobb angle changed by less than 5 degrees (non-progression group, 30 patients). The X-ray images of three regions of interest (ROIs) (lung [ROI1], abdomen [ROI2], and total spine [ROI3]), were used as the source data for learning and prediction. Five spine surgeons also predicted the progression of scoliosis by reading the X-rays in a blinded manner.

Results

The prediction performance of the DCNN for AIS curve progression showed an accuracy of 69% and an area under the receiver-operating characteristic curve of 0.70 using ROI3 images, whereas the diagnostic performance of the spine surgeons showed inferior at 47%. Transfer learning with a pretrained DCNN contributed to improved prediction accuracy.

Conclusion

Our developed method to predict the risk of scoliosis progression in AIS by using a DCNN could be a valuable tool in decision-making for therapeutic interventions for AIS.

DOI： 10.1186/s12891-022-05565-6

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Other Link： https://link.springer.com/article/10.1186/s12891-022-05565-6/fulltext.html

Language：English   Publishing type：Research paper (scientific journal)   Publisher：IMEKO International Measurement Confederation  

<p class="Abstract"><span lang="EN-US">We investigated the relationship between the spatial-resolution property of soft tissue images and the lesion detection ability using U-net. We aimed to explore the possibility of dose reduction during energy subtraction chest radiography. The correlation between the spatial-resolution property of each dose image and the segmentation accuracy of the tumor area in the four regions where the tumor was placed was evaluated using linear regression analysis. The spatial-resolution property was determined by task-based evaluation, and the task-based modulation transfer function (TTF) was computed as its index. TTFs of the reference dose image and the 75 % dose image showed almost the same frequency characteristics regardless of the location of the tumor, and the Dice coefficient also high. When the tumor was located in the right supraclavicular region and under 50 % dose, the frequency characteristics were significantly reduced, and the Dice coefficient was also low. Our results showed a close relationship between the spatial-resolution property and the segmentation accuracy of tumor area using deep learning in dual-energy subtraction chest radiography. In conclusion, a dose reduction of approximately 25 % compared to the conventional method can be achieved. The limitations are the shape of the simulated mass and the use of chest phantom.</span></p>

DOI： 10.21014/acta_imeko.v11i2.1168

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Language：English   Publishing type：Research paper (scientific journal)  

This study aimed to determine whether a U-Net-based segmentation method could be used to automatically extract regions of the whole heart and atrioventricular regions from pediatric cardiac computed tomography images with high accuracy. Pediatric cardiac contrast computed tomography images with no abnormalities (n = 20; patient age, 0-13 years; mean 5 years) were used for segmentation of the whole heart and each atrioventricular region using U-Net. Segmentation accuracy was evaluated using the Dice similarity coefficient. The mean Dice similarity coefficient for the whole-heart segmentation was high at 0.95. There were no significant differences between age categories. The median Dice similarity coefficients for segmentation of the atria and ventricles were good (> 0.86). There were significant differences between age categories at some sites. Differences in the Dice similarity coefficient may have occurred because the target diseases and examination procedures differed according to subject age. There was no clear tendency for similar values between subjects of school age, close to adulthood, and newborns; good agreement was obtained in all age categories. These results suggest that U-Net-based segmentation may be useful for automatic extraction of the whole heart and atrioventricular regions from pediatric computed tomography images.

DOI： 10.1007/s12194-022-00657-3

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：IMEKO International Measurement Confederation  

<p class="Abstract">Sterilization of medical equipment in isolation wards is essential to prevent the transmission of severe acute respiratory syndrome coronavirus 2 (SARS–CoV-2) infection. Particularly, the radiographic console of portable X-ray machines requires frequent disinfection because it is regularly moved; this requires considerable infection control effort as the number of patients with coronavirus disease 2019 (COVID-19) increases. To evaluate the application of a system facilitating noncontact operation of radiographic consoles for patients with COVID-19 to reduce the need for frequent disinfection. We developed a noncontact operation system for radiographic consoles that used a common eye tracker. We compared calibration errors between with and without face shield conditions. Moreover, the use of console operation among 41 participants was investigated. The calibration error of the eye tracker between with and without face shield conditions did not significantly differ. All (<em>n</em> = 41) observers completed the console operation. Pearson’s correlation coefficient analysis showed a strong correlation (<em>r</em> = 0.92, <em>P</em> < 0.001) between the average operation time and the average number of misoperations. Our system that used an eye tracker can be applied even if the operator uses a face shield. Thus, its application is important in preventing the transmission of infection.</p>

DOI： 10.21014/acta_imeko.v11i2.1272

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Language：English   Publishing type：Research paper (scientific journal)  

BACKGROUND: Head computed tomography (CT) is a commonly used imaging modality in radiology facilities. Since multiplanar reconstruction (MPR) processing can produce different results depending on the medical staff in charge, there is a possibility that the antemortem and postmortem images of the same person could be assessed and identified differently. OBJECTIVE: To propose and test a new automatic MPR method in order to address and overcome this limitation. METHODS: Head CT images of 108 cases are used. We employ the standardized transformation of statistical parametric mapping 8. The affine transformation parameters are obtained by standardizing the captured CT images. Automatic MPR processing is performed by using this parameter. The sphenoidal sinus of the orbitomeatal cross section of the automatic MPR processing of this study and the conventional manual MPR processing are cropped with a matrix size of 128×128, and the value of zero mean normalized correlation coefficient is calculated. RESULTS: The computed zero mean normalized cross-correlation coefficient (Rzncc) of≥0.9, 0.8≤Rzncc <  0.9 and 0.7≤Rzncc <  0.8 are achieved in 105 cases (97.2%), 2 cases (1.9%), and 1 case (0.9%), respectively. The average Rzncc was 0.96±0.03. CONCLUSION: Using the proposed new method in this study, MPR processing with guaranteed accuracy is efficiently achieved.

DOI： 10.3233/XST-221142

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Language：Japanese   Publisher：(公社)日本放射線技術学会  

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Other Link： https://search.jamas.or.jp/default/link?pub_year=2022&ichushi_jid=J01192&link_issn=&doc_id=20220126400003&doc_link_id=1390853741275705216&url=https%3A%2F%2Fcir.nii.ac.jp%2Fcrid%2F1390853741275705216&type=CiNii&icon=https%3A%2F%2Fjk04.jamas.or.jp%2Ficon%2F00003_3.gif

Language：Japanese   Publishing type：Research paper (scientific journal)  

PURPOSE: Accurate positioning is essential for radiography, and it is especially important to maintain image reproducibility in follow-up observations. The decision on re-taking radiographs is entrusting to the individual radiological technologist. The evaluation is a visual and qualitative evaluation and there are individual variations in the acceptance criteria. In this study, we propose a method of image evaluation using a deep convolutional neural network (DCNN) for skull X-ray images. METHOD: The radiographs were obtained from 5 skull phantoms and were classified by simple network and VGG16. The discrimination ability of DCNN was verified by recognizing the X-ray projection angle and the retake of the radiograph. DCNN architectures were used with the different input image sizes and were evaluated by 5-fold cross-validation and leave-one-out cross-validation. RESULT: Using the 5-fold cross-validation, the classification accuracy was 99.75% for the simple network and 80.00% for the VGG16 in small input image sizes, and when the input image size was general image size, simple network and VGG16 showed 79.58% and 80.00%, respectively. CONCLUSION: The experimental results showed that the combination between the small input image size, and the shallow DCNN architecture was suitable for the four-category classification in X-ray projection angles. The classification accuracy was up to 99.75%. The proposed method has the potential to automatically recognize the slight projection angles and the re-taking images to the acceptance criteria. It is considered that our proposed method can contribute to feedback for re-taking images and to reduce radiation dose due to individual subjectivity.

DOI： 10.6009/jjrt.780104

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：Elsevier BV  

DOI： 10.1016/j.measen.2021.100089

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：Elsevier BV  

DOI： 10.1016/j.measen.2021.100127

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Publishing type：Research paper (international conference proceedings)   Publisher：SPIE  

DOI： 10.1117/12.2581424

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Public Library of Science (PLoS)  

<sec id="sec001"><title>Objective</title>Despite the high risk of missing lesions in mammography, the missed lesion rate is yet to be clinically established. Further, no breast phantoms with adjustable breast density currently exist. We developed a novel, adjustable-density breast phantom with a composition identical to that of actual breasts, and determined the quantitative relationship between breast density and the missed lesion rate in mammography.

</sec><sec id="sec002"><title>Methods</title>An original breast phantom consisting of adipose- and fibroglandular-equivalent materials was developed, and a receiver operating characteristic (ROC) study was performed. Breast density, which is the fraction by weight of fibroglandular to total tissue, was adjusted to 25%, 50%, and 75% by arbitrarily mixing the two materials. Microcalcification, mass lesions, and spiculated lesions, each with unique characteristics, were inserted into the phantom. For the above-mentioned fibroglandular densities, 50 positive and 50 negative images for each lesion type were used as case samples for the ROC study. Five certified radiological technologists participated in lesion detection.

</sec><sec id="sec003"><title>Results</title>The mass-lesion detection rate, according to the area under the curve, decreased by 18.0% (<italic>p</italic>= 0.0001, 95% Confidence intervals [CI] = 0.1258 to 0.1822) and 37.8% (<italic>p</italic>= 0.0003, 95% CI = 0.2453 to 0.4031) for breast densities of 50% and 75%, respectively, compared to that for a 25% breast density. A similar tendency was observed with microcalcification; however, spiculated lesions did not follow this tendency.

</sec><sec id="sec004"><title>Conclusions</title>We quantified the missed lesion rate in different densities of breast tissue using a novel breast phantom, which is imperative for advancing individualized screening mammography.

</sec>

DOI： 10.1371/journal.pone.0245060

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Springer Science and Business Media LLC  

Bedside radiography has increasingly attracted attention because it allows for immediate image diagnosis after X-ray imaging. Currently, wireless flat-panel detectors (FPDs) are used for digital radiography. However, adjustment of the X-ray tube and FPD alignment are extremely difficult tasks. Furthermore, to prevent a poor image quality caused by scattered X-rays, scatter removal grids are commonly used. In this study, we proposed a scatter-correction processing method to reduce the radiation dose when compared with that required by the X-ray grid for the segmentation of a mass region using deep learning during bedside chest radiography. A chest phantom and an acrylic cylinder simulating the mass were utilized to verify the image quality of the scatter-corrected chest X-rays with a low radiation dose. In addition, we used the peak signal-to-noise ratio and structural similarity to quantitatively assess the quality of the low radiation dose images compared with normal grid images. Furthermore, U-net was used to segment the mass region during the scatter-corrected chest X-ray with a low radiation dose. Our results showed that when scatter correction is used, an image with a quality equivalent to that obtained by grid radiography is produced, even when the imaging dose is reduced by approximately 20%. In addition, image contrast was improved using scatter radiation correction as opposed to using scatter removal grids. Our results can be utilized to further develop bedside chest radiography systems with reduced radiation doses.

DOI： 10.1007/s12194-020-00586-z

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Other Link： http://link.springer.com/article/10.1007/s12194-020-00586-z/fulltext.html

Language：Japanese   Publishing type：Research paper (bulletin of university, research institution)  

CiNii Article

CiNii Books

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Other Link： http://id.ndl.go.jp/bib/031224466

Publishing type：Research paper (scientific journal)   Publisher：Springer Science and Business Media LLC  

DOI： 10.1007/s11604-020-00986-6

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Other Link： https://link.springer.com/article/10.1007/s11604-020-00986-6/fulltext.html

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：SPIE  

This study is aimed to automatically segment mammary gland region into scattered mammary glands and fatty breasts using deep learning method. Total 433 mediolateral oblique-view mammograms of Japanese women were collected and confirmed for scattered mammary glands or fatty breasts; using BI-RADS's classification. First, manually contoured mammary gland regions were determined for all mammograms as ground truths by three certified radiological technologists. Second, the U-net model was employed to segment the mammary gland region automatically. This model is a type of convolutional neural network (CNN) mainly aimed at medical image segmentation. The segmentation accuracies were assessed based on five criteria, Dice coefficients, breast densities, mean gray values, centroids, and sizes of mammary gland region. The Dice coefficient was 0.915. The mean size of mammary gland regions obtained by the Unet was 8.7% larger than that of the ground truths. The mean centroid coordinates of mammary gland regions by the U-net were shifted 1.6 and 5.4 mm on average in mediolateral and craniocaudal directions, respectively from ground truths. The mean gray value of mammary gland regions obtained by the U-net was only 0.4% higher compared with ground truths. The resultant difference was 0.4% on average in breast densities between ground truths and the segmented mammary gland regions. We found significant similarity in the ground truths and the data generated by deep learning on all the parameters, thereby attesting the efficacy of this method for segmenting the mammary gland regions of not only the dense breasts but also the scattered mammary gland- and fatty- breasts.

DOI： 10.1117/12.2562180

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：SPIE  

Receiver operating characteristic (ROC) examination was performed to investigate the effectiveness of high-luminance monitors in digital X-ray mammography. For this purpose, an original breast phantom consisting of adipose and fibroglandular equivalent tissues with an identical X-ray absorption characteristic over the entire mammographic photon energy range was developed. Furthermore, the phantom's fibroglandular density and distribution could be changed arbitrarily. Three types of lesions, microcalcification, mass, and spiculated, were inserted into the breast phantom, and the ROC examination was performed by five radiological technologists certified in screening mammography, to obtain the area under the curve. A liquid crystal display (LCD) monitor with 5 megapixels in a 21-inch display size calibrated to a grayscale standard display function curve was used for the observation. The monitor was set to 600, 900, and 1200 cd/m(2) in maximum luminance. The experimental details were fibroglandular density of 25%, respective 50 positive and negative images, and free observation time and distance. As a result, the dependence on monitor luminance differed according to the lesion type. The detectability of microcalcification increased with the increase in the luminance of the monitor. Spiculated lesions were similar for all luminance changes. The detectability of mass lesions was significantly higher at 900 cd/m(2) than at 600 cd/m(2). There was no significant difference between those at 900 cd/m(2) and 1200 cd/m(2). In conclusion, the maximum luminance of the diagnostic LCD monitor for mammography should be at least 900 cd/m(2) to guarantee stable detectability.

DOI： 10.1117/12.2555276

Web of Science

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Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1007/s11604-019-00894-4

Scopus

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Language：Japanese   Publisher：(公社)日本放射線技術学会  

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：MEDICAL IMAGING AND INFORMATION SCIENCES  

Unsharpnesses are likely to occur with a high heart rate in angiography. In this study, U-Net was used to remove unsharpness for the purpose of improving the image quality of x-ray movies in the cardiovascular imaging. Dynamic x-ray images including unsharpness were taken with the moving speed of the metronome at 100, 200 beats/minute （bpm）. Standard deviation（SD）and modulation transfer function（MTF）were measured and used to evaluate the effect of artifact removal. As a result, mean SDs of original images and processed images by U-Net were 4.34 and 0.54, respectively. Similarly, mean cut-off frequencies of MTF of original images and processed images by U-Net were 0.52 mm⁻¹and 4.6 mm⁻¹, respectively. Since SD was greatly reduced and MTF was greatly improved, U-Net would improve the image quality of improvement cardiovascular dynamic x-ray images.

DOI： 10.11318/mii.36.98

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Other Link： https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-17K17738/

Authorship：Corresponding author   Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：MEDICAL IMAGING AND INFORMATION SCIENCES  

The purpose of this paper is to develop a computerized classification method for right or left and directions of arms in forearm X-ray images using a deep convolutional neural network（DCNN）. 648 radiographs were obtained by using X-ray lower arm phantoms. These images were downsized to 213×256 pixels and used as training and test images in the DCNN. AlexNet and GoogLeNet were used as the DCNN. All radiographs were classified to eight categories by the DCNN. Classification accuracies were obtained by nine-fold cross validation tests. The accuracies using AlexNet and GoogLeNet were 79.3% and 92.6%, respectively. GoogLeNet would be useful to classify forearm radiographs automatically. The proposed method may contribute to quality assurance for medical images.

DOI： 10.11318/mii.36.83

CiNii Article

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Language：Japanese   Publishing type：Research paper (scientific journal)  

DOI： 10.11318/mii.36.64

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Language：English   Publishing type：Research paper (international conference proceedings)  

DOI： 10.1117/12.2507351

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Language：Japanese   Publishing type：Research paper (scientific journal)  

DOI： 10.11409/mit.36.217

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Authorship：Lead author   Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Japanese Society of Radiological Technology  

Countermeasures against respiratory movement are important for tumors of thorax and abdomen in stereotactic body radiation therapy. In the present paper, a web-camera-based-respiratory monitoring method without contact with patient’s body was proposed for respiratory study. Thoracic and abdominal motion images were taken by a web camera, and were analyzed using simple image-processing techniques for obtaining respiratory waveforms. Four motion images with different respiration rate were obtained from resusci anne simulator. Respiration waveforms were estimated from the moving images by the proposed method, and were compared with respiration waveforms obtained by the conventional respiratory monitoring device. That was found to have a strong correlation. In addition, the two waveforms were similar in Bland–Altman method comparison. The proposed method can provide non-contact, non-invasive, simple, and realistic respiratory monitoring system for radiotherapy.

DOI： 10.6009/jjrt.2018_JSRT_74.11.1286

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Other Link： http://id.ndl.go.jp/bib/029359646

Language：Japanese   Publishing type：Research paper (scientific journal)  

In computed tomography coronary angiography (CTCA), calcification and stent make it difficult to evaluate intravascular lumen. This is a cause of low positive-predictive value of coronary stenosis. Therefore, it is expected to develop a computer-aided diagnosis (CAD) system that can automatically detect stenosis in coronary arteries. The purpose of this study is to automatically recognize calcifications or stents in coronary arteries and classify them from the normal coronary artery in CTCA. We used 4960 coronary-cross-sectional images, which consisted of 1113 images with calcification, 1353 images with a stent, and 2494 normal artery images. These images were automatically classified using the deep convolutional neural network (LeNet, AlexNet, and GoogLeNet). The classification accuracy of LeNet, AlexNet, and GoogLeNet were 58.4%, 75.9%, and 81.3%, respectively. The proposed method would be a fundamental technique of CAD in CTCA.

DOI： 10.6009/jjrt.2018_JSRT_74.10.1138

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：American Scientific Publishers  

DOI： 10.1166/jmihi.2018.2398

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DOI： 10.14923/transinfj.2017IGL0001

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DOI： 10.6009/jjrt.2017_JSRT_73.11.1125

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Authorship：Lead author   Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：MEDICAL IMAGING AND INFORMATION SCIENCES  

The purpose of this study is to investigate an effectiveness of a method for automatic classification of infant hip types on ultrasonography. A convolutional neural network（CNN）was adopted for the automated classification of hip types corresponding to the Graf method that was defacto standard method for ultrasonographic assessment of infant hip dysplasia. In the CNN, AlexNet was employed as neural network model. We collected 49 ultrasound images that were classified based on the Graf method by an ultrasonographer. Data augmentation by rotating, mirroring, adjusting contrast, etc., generated additional 246,960 images from the original 49 ones. The augmented images were used as training data of the CNN. The accuracy by 10-fold cross validation was 73%. The CNN would be potentially effective for automatic classification of infant hip types.

DOI： 10.11318/mii.34.92

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Other Link： https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-16K09012/

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DOI： 10.4236/jbise.2017.103009

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Language：Japanese   Publishing type：Research paper (scientific journal)  

DOI： 10.11409/mit.36.32

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：MEDICAL IMAGING AND INFORMATION SCIENCES  

<p>The purpose of this study is to investigate and compare the effectiveness of two previously proposed waveletbased medical image enhancement methods,<i> i.e</i>., exponential-type （E-type） and sigmoid-type （S-type） mapping methods. A total of 30 chest radiographs, CT images and mammograms were evaluated visually by using Scheffe's method for paired comparison. As a visual evaluation, images obtained with and without enhancement processing, or images processed with the two enhancement methods were displayed side by side on a light emitting diode monitor. Two different images, <i>i.e</i>.,original image vs. image processed with E-type mapping method, original image vs. image processed with S-type mapping method, and image processed with E-type mapping method vs. that with S-type mapping method, were then evaluated on a discrete rating scale. The experimental results showed that the images processed with S-type mapping method are significantly better than the original images obtained with the three different modalities in both the visual and quantitative evaluations. In addition, the images processed with E-type mapping method are significantly better than the original images of chest radiographs in both the evaluations. The results demonstrate that the previously proposed image enhancement methods are effective and feasible.</p>

DOI： 10.11318/mii.33.63

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The purpose of this study is to develop an automated selection method for cross‐sectional images with basal ganglia from brain CT scan. The proposed method includes binarization, morphological operation and labeling techniques. Area was calculated from the labeled region inside the cranial bones. The cross‐sectional images with basal ganglia were automatically selected using the calculated area. The method was applied to 22 cases each with 20 slices. As a result, the sensitivity and the specificity were 0.95 and 0.98 respectively. The proposed method would be a fundamental technique for the development of computer‐aided diagnosis（CAD）system.

DOI： 10.11318/mii.33.16

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Springer Tokyo  

The volume of the temporal horn of the lateral ventricle (THLV) on brain computed tomography (CT) images is important for neurologic diagnosis. Our purpose in this study was to develop a z-score-based semi-quantitative analysis for estimation of the THLV volume by using voxel-based morphometry. The THLV volume was estimated by use of a z-score mapping method that consisted of four main steps: anatomic standardization, construction of a normal reference database, calculation of the z score, and calculation of the mean z score in a volume of interest (VOI). A mean z score of the CT value obtained from a VOI around the THLV was used as an index for the THLV volume. CT scans from 50 subjects were evaluated. For evaluation of the accuracy of this method for estimating the THLV volume, the THLV volume was determined manually by neuroradiologists (serving as the reference volume). A mean z score was calculated from the VOI for each THLV of the 50 subjects by use of the proposed method. The accuracy of this method was evaluated by use of the relationship between the mean z score and the reference volume. The quadratic polynomial regression equation demonstrated a statistically significant correlation between the mean z score and the reference volume of the THLV (R2 = 0.94
P &lt
 0.0001). In 92 of 100 THLVs (92 %), the 95 % prediction interval of the regional mean z score captured the reference volume of the THLV. The z-score-based semi-quantitative analysis has the potential quantitatively to estimate the THLV volume on CT images.

DOI： 10.1007/s12194-015-0335-0

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Japanese Society of Radiological Technology  

CT perfusion (CTP) is obtained cerebrovascular circulation image for assessment of stroke patients; however, at the expense of increased radiation dose by dynamic scan. Iterative reconstruction (IR) method is possible to decrease image noise, it has the potential to reduce radiation dose. The purpose of this study is to assess the visual effect of IR method by using a digital perfusion phantom. The digital perfusion phantom was created by reconstructed filtered back projection (FBP) method and IR method CT images that had five exposure doses. Various exposure dose cerebral blood flow (CBF) images were derived from deconvolution algorithm. Contrast-to-noise ratio (CNR) and visual assessment were compared among the various exposure dose and each reconstructions. Result of low exposure dose with IR method showed, compared with FBP method, high CNR in severe ischemic area, and visual assessment was significantly improvement. IR method is useful for improving image quality of low-dose CTP.

DOI： 10.6009/jjrt.2015_JSRT_71.11.1063

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DOI： 10.4236/jbise.2015.810067

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DOI： 10.4236/health.2015.76078.

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DOI： 10.4236/health.2015.72026

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DOI： 10.4236/health.2015.71004

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Language：Japanese   Publisher：(公社)日本放射線技術学会  

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Authorship：Corresponding author   Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Japanese Society of Radiological Technology  

Objective evaluation, e.g., using the modulation transfer function (MTF) or the noise power spectrum (NPS) of an X-ray imaging system may not correctly correspond to the subject's evaluation, e.g., when using the receiver operating characteristic (ROC). Moreover, it is difficult to measure MTF or NPS from clinical images. We therefore applied MTF fractal dimension to an X-ray imaging system. The MTF fractal dimension includes the frequency properties of the human eye in addition to quantitative complexity. In this study, we demonstrated a relationship between basic image quality and MTF fractal dimension using simulated and actual X-ray images.

DOI： 10.6009/jjrt.2014_JSRT_70.3.250

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Authorship：Corresponding author   Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Japanese Society of Radiological Technology  

In this paper, we propose a detection method for blurred regions in radiographs. The method involves edge detection using a Sobel filter, manually determining the region of interest (ROI), feature calculation, and classification using a support vector machine. We applied our method to 14 phantom images (7 normal images, 7 blurred images) and 14 clinical images (12 normal images, 2 blurred images). As a result, the average classification accuracies of ROIs with blurring and ROIs without blurring were 98% and 90% for phantom images and clinical images, respectively.

DOI： 10.6009/jjrt.2014_JSRT_70.3.254

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Other Link： http://search.jamas.or.jp/link/ui/2014238123

Language：English   Publishing type：Research paper (scientific journal)   Publisher：Springer-Verlag Tokyo  

The hyperdense middle cerebral artery (MCA) dot sign representing a thromboembolus is one of the important computed tomography (CT) findings for acute stroke on unenhanced CT images. Our purpose in this study was to develop an automated method for detection of the MCA dot sign of acute stroke on unenhanced CT images. The algorithm of the method which we developed consisted of 5 major steps: extraction of the sylvian fissure region, initial identification of MCA dots based on the morphologic top-hat transformation, feature extraction of candidates, elimination of false positives (FPs) by use of a rule-based scheme, and classification of candidates using a support vector machine (SVM) classifier with four features. Our database comprised 297 CT images obtained from seven patients with the MCA dot sign. The performance of this scheme for classification of the MCA dot sign was evaluated by means of a leave-one-case out method. The performance of the classification by use of the SVM achieved a maximum sensitivity of 97.5 % (39/40) at a FP rate of 1.28 per image. The sensitivity for detection of the MCA dot sign was 97.5 % (39/40) with a FP rate of 0.5 per hemisphere. The method we developed has the potential to detect the MCA dot sign of acute stroke on unenhanced CT images. © Japanese Society of Radiological Technology and Japan Society of Medical Physics 2013.

DOI： 10.1007/s12194-013-0234-1

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：Springer Verlag  

The realities of physical and psychological burden associated with mammography are not fully understood. We have measured the muscle activity and the sympathetic nervous activity of subjects during mammography to estimate the burden. The experimental results suggested that positioning during mammography affects the muscle activity and the sympathetic nervous activity of the body. We carried out another preliminary experiment for decreasing the examinee's burden using humorous video. In the experiment, two groups ("humor group" and "neutral group") underwent mammography. The humor group was shown a humorous video during mammography. As a result, numerical rating scale scores of humor group on pain and experience time were higher than that of neutral group (no significant difference). In conclusion, the physical and psychological burden of mammography examinees could be evaluated by measuring the muscle activity and the sympathetic nervous activity. Humorous video may be effective at increasing pain tolerance of subjects during mammography. © 2014 Springer International Publishing.

DOI： 10.1007/978-3-319-07887-8_71

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Language：Japanese   Publisher：(公社)日本放射線技術学会  

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DOI： 10.4236/health.2013.58181

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：SPRINGER  

In this work, the authors present an effective denoising method to attempt reducing the noise in mammographic images. The method is based on using hierarchical correlation of the coefficients of discrete stationary wavelet transforms. The features of the proposed technique include iterative use of undecimated multi-directional wavelet transforms at adjacent scales. To validate the proposed method, computer simulations were conducted, followed by its applications to clinical mammograms. Mutual information originating from information theory was used as an evaluation measure for selection of an optimal wavelet basis function. We examined the performance of the proposed method by comparing it with the conventional undecimated discrete wavelet transform (UDWT) method in terms of processing time-consuming and image quality. Our results showed that with the use of the proposed method the computation time can be reduced to approximately 1/10 of the conventional UDWT method consumed. The results of visual assessment indicated that the images processed with the proposed UDWT method showed statistically significant superior image quality over those processed with the conventional UDWT method. Our research results demonstrate the superiority and effectiveness of the proposed approach.

DOI： 10.1007/s10278-012-9555-6

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In this work the authors present an effective denoising method to attempt to reduce the noise in mammographic images. The method is based on using hierarchical correlation of the coefficients of discrete stationary wavelet transforms. The features of the proposed technique include iterative use of undecimated multi-directional wavelet transforms at adjacent scales. To validate the proposed method, computer simulations were conducted, followed by its applications to clinical mammograms. Mutual information originating from information theory was used as an evaluation measure in the present study. Moreover, we conducted a perceptual evaluation of the processed images obtained from the proposed method and other conventional methods for confirmation of the effectiveness of the proposed approach. The experimental results show that our proposed method has the potential to effectively reduce noise while maintaining high-frequency information of original images. © 2013 Springer-Verlag.

DOI： 10.1007/978-3-642-29305-4_229

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Authorship：Lead author   Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：The Institute of Electronics, Information and Communication Engineers  

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Other Link： http://search.jamas.or.jp/link/ui/2013307664

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

The purpose of this study was to evaluate the performance of a conventional discrete wavelet transform (DWT) method and a modified undecimated discrete wavelet transform (M-UDWT) method applied to mammographic image denoising. Mutual information, mean square error, and signal to noise ratio were used as image quality measures of images processed by the two methods. We examined the performance of the two methods with visual perceptual evaluation. A two-tailed F test was used to measure statistical significance. The difference between the M-UDWT processed images and the conventional DWT-method processed images was statistically significant (P&lt
0.01). The authors confirmed the superiority and effectiveness of the M-UDWT method. The results of this study suggest the M-UDWT method may provide better image quality as compared to the conventional DWT. © 2013 IEEE.

DOI： 10.1109/EMBC.2013.6610272

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The amount of radiation dose to the patient from digital radiography is of great concern. In particular, it is important to keep the radiation dose exposure to a minimum for patients in their reproductive period, who frequently undergo repeated radiation exposure during the course of diagnostic imaging and treatment follow-up. However, there is a well-recognized trade-off between image quality and radiation dose. The balancing of dose and image quality should be performed explicitly to ensure that patient doses are kept as low as reasonable achievable, while maintaining a clinically acceptable image quality. In response to this issue, many researchers have conducted extensive studies on developing image processing methods. In this paper, we propose an improved wavelet-transform-based method for offering a possibility to reduce the radiation dose while maintaining a clinically acceptable image quality. The proposed method integrates the advantages of our previously proposed wavelet-coefficient weighted method and the existing BayesShrink thresholding method. To verify the effectiveness of the proposed method, we measured and compared the presampled modulation transfer functions and the noise power spectra (NPS) of the processed computed radiography images. Furthermore, variations of contrast and NPS with respect to radiation dose were also examined. Visual evaluations were also performed by five experienced radiological technologists. Experimental results demonstrated that the proposed method could improve the resolution characteristic while keeping the noise level within an acceptable limit. Our visual evaluation showed that an approximately 40% reduction in exposure dose might be achieved with the proposed method in hip joint and lumbar spine radiographs. © 2013 Springer-Verlag.

DOI： 10.1007/978-3-642-29305-4_233

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Improving image quality in digital mammographic images has clinical impact in order to increase accuracy of detection of breast cancer. This study aimed to develop and evaluate a new method for denoising mammographic images. The features of the proposed method include iterative use of undecimated multidirectional wavelet transforms at adjacent scales. In this method, computer-based simulations have been carried out for selecting wavelet basis function based on mutual information metric. Perceptual experiments on clinical mammograms were conducted. This new method was compared with the conventional methods to demonstrate its superiority.

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This study presents an improved wavelet-transform-based method for offering a possibility to reduce the radiation dose while maintaining a clinically acceptable image quality. The proposed method integrates a straightforward extension of our previously proposed wavelet-coefficient weighted method and the existing BayesShrink thresholding method. Experimental results demonstrated that the proposed method could improve the resolution characteristic while keeping the noise level within an acceptable limit. Our visual evaluation also showed that an approximately 40% reduction in exposure dose could be achieved with the proposed method in hip joint and lumbar spine radiographs.

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：TOHOKU UNIV MEDICAL PRESS  

Mammography has become widespread as a standard method for breast cancer screening. For women undergoing mammography, compression of the breast and special positioning are requested, and they cause the physical burden and pain. However, the reality of the physical burden and subjective pain associated with mammography are not fully understood. We therefore measured the muscle activity of subjects during positioning for mammography screening using surface electromyography to evaluate the physical burden and pain associated with the positioning. The subjects consisted of 15 women (age: 44.4 +/- 6.56 years old, height: 160 +/- 6.7 cm, weight: 55.08 +/- 3.94 kg, and body mass index: 21.4 +/- 2.21). Measurements were performed in the mediolateral oblique position, a standard position for mammography. The target muscles were the sternocleidomastoid, biceps, trapezius and gastrocnemius muscles. A portable multi-purpose bio-amplifier was used for the measurements. Visual analogue scale (VAS), which is a tool for self-assessment of subjective pain, was used for pain measurement. The analysis of variance showed the significant difference in the amounts of muscle activities in all the target muscles between the relaxation phase before mammography positioning and the stress phase during mammography positioning. The sites with the increased muscle activities were consistent with the sites of pain measured with the VAS. These results suggest that positioning during mammography affects the muscle activity and that the increased muscle activity could be related to the pain. Understanding muscle activities during mammography is invaluable in making the pain reduction program for the subjects undergoing mammography.

DOI： 10.1620/tjem.228.53

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Authorship：Lead author,　Corresponding author   Language：English   Publishing type：Research paper (scientific journal)  

In Japan, radiologists and radiologic technologists are endeavoring to improve the quality of lung CT screening. In particular, preliminary screening by radiologic technologists is expected to decrease radiologists' burden and improve the accuracy of CT screening. We considered that an application of computer-aided detection (CAD) would also be as useful in preliminary screening as in the radiologist's regular reading. Our purpose in this study was to investigate the potential of the application of CAD to preliminary screening. CAD software that we developed was applied to 17 lung CT scans that radiologic technologists had pre-interpreted. A radiologist recognized 29 lung nodules from the CT images, whereas radiologic technologists did not recognize 11 of the 29 nodules at their pre-reading. Our CAD software detected lung nodules at an accuracy of 100% (29/29), with 4.1 false positives per case. The 11 nodules that radiologic technologists did not recognize were included in the CAD-detected nodules. This result suggests that the application of CAD may aid radiologic technologists in their preliminary screening. © Japanese Society of Radiological Technology and Japan Society of Medical Physics 2012.

DOI： 10.1007/s12194-012-0145-6

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Language：Japanese   Publisher：一般社団法人電子情報通信学会  

This study presents an improved wavelet-transform-based method for offering a possibility to reduce the radiation dose while maintaining a clinically acceptable image quality. The proposed method integrates a straightforward extension of our previously proposed wavelet-coefficient weighted method and the existing BayesShrink thresholding method. Experimental results demonstrated that the proposed method could improve the resolution characteristic while keeping the noise level within an acceptable limit. Our visual evaluation also showed that an approximately 50% reduction in exposure dose could be achieved with the proposed method in hip joint and lumbar spine radiographs.

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Our purpose in this study was to develop a computer-aided detection scheme for identification of hypoattenuation of acute stroke on unenhanced CT images to select patients for thrombolysis of acute stroke. This method is based on a z-score mapping method. The algorithm of the developed method consisted of five main steps: anatomic standardization, calculation of the z-score with a normal reference database, extraction of candidate voxels for hypoattenuation, feature extraction, and classification. The territory of the middle cerebral artery was divided into ten specified regions, according to a visually quantitative CT scoring system, the Alberta Stroke Programme Early CT Score (ASPECTS) method. Each of the ASPECTSdefined regions was classified as hypoattenuation or normality by linear discriminate analysis. The method was applied to 26 patients who had hypoattenuation areas (&lt
6 h). The performance of this scheme for classification of hypoattenuation was evaluated using a leave-one-case-out method. As a result, an average sensitivity of 89.7% and an average specificity of 85.2% for automatically classifying hypoattenuation regions in the lentiform nucleus and the insular regions were obtained, and the average accuracy for the classification of hypoattenuation per patient was 84.6% (range 55.6-100%). The newly developed method has the potential accurately to identify hypoattenuation of acute stroke in the ASPECTS-defined regions. © Japanese Society of Radiological Technology and Japan Society of Medical Physics 2011.

DOI： 10.1007/s12194-011-0143-0

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In this report, we propose an effective denoising method to attempt to denoise mammographic images. The method is based on using hierarchical correlation of the coefficients of discrete stationary wavelet transforms. The features of the proposed technique include iterative use of undecimated multi-directional wavelet transforms at adjacent scales. To validate the proposed method, computer simulations were conducted, followed by its applications to clinical mammograms. Mutual information was used as an evaluation measure in the present study. The results show that the proposed method has the potential to effectively reduce noise while maintaining high-frequency information.

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Japanese Society of Radiological Technology  

This study focused on measuring examinees' muscle activities during mammography positioning using surface electromyography. Muscle activities were measured in three women (40–50s) in two-view mammography (MLO: mediolateral oblique, CC: craniocaudal). The muscles measured were the sternocleidomastoid, biceps, trapezius, and gastrocnemius, selected based on the visual analogue scale reported by Sharp et al. We used a multi-purpose portable bio-amplifier (Polymate AP1000) to assess the muscle activities. The results showed that the trapezius in right MLO and sternocleidomastoid in right CC were active in all three subjects. This suggests that the muscles directly related to mammography positioning are highly active. In addition, the gastrocnemius was active throughout the mammography. The biceps and gastrocnemius were also active in at least one of the three women. We believe that quantitative assessment of muscle activities during mammography positioning will contribute to the improvement of pain-reduction programs in mammography.

DOI： 10.6009/jjrt.67.679

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：MEDICAL IMAGING AND INFORMATION SCIENCES  

In this paper, we investigate the effect of the use of wavelet transform for image processing on radiation dose reduction in computed radiography(CR), by measuring various physical characteristics of the wavelet-transformed images. Moreover, we propose a wavelet-based method for offering a possibility to reduce radiation dose while maintaining a clinically acceptable image quality. The proposed method integrates the advantages of two previously proposed techniques, <i>i.e.</i>, sigmoid-type transfer curve for wavelet coefficient weighting adjustment technique, as well as a wavelet soft-thresholding technique. The former can improve contrast and spatial resolution of CR images, the latter is able to decrease image noise. In the investigation of physical characteristics, we measured and compared the modulation transfer function, noise power spectrum, and contrast-to-noise ratio of CR images obtained by the proposed method and other different methods. Furthermore, visual evaluation was performed using Scheffe's pair comparison method. Experimental results showed that the proposed method could improve overall image quality as compared to other methods. Our visual evaluation showed that an approximately 40% reduction in exposure dose might be achieved in hip joint radiography by using the proposed method.

DOI： 10.11318/mii.28.51

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Language：Japanese   Publishing type：Research paper (bulletin of university, research institution)  

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：The Japanese Society of Medical Imaging Technology  

This paper described a z-score mapping method on the basis of a voxel-by-voxel analysis to visualize hypoattenuation regions of hyperacute stroke on unenhanced CT images. The algorithm of this method consisted of 5 major steps, <I>i.e</I>., anatomic standardization, construction of a normal reference database, calculation of z score, elimination of false positive areas, and extraction of hypoattenuation areas. The performance of this method in detection of hypoattenuation with a series of 21 patients with infarction (< 3 hours) showed the AUC =0.834 for distinction between hypoattenuation and normal regions. The result of an observer study with five neuroragiologists, also, demonstrated the average AUC for detection oh hypoattenuation regions significantly improved from 0.883 to 0.925 (<I>P</I>< 0.01). Therefore, the z-score mapping method could effectively extract hypoattenuation regions that showed a high z-score value on the z-score map. The use of this method has the potential to help neuroradiolgists detect hypoattenuation regions of hyperacute stroke on unenhanced CT images.

DOI： 10.11409/mit.29.17

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Language：English   Publishing type：Research paper (international conference proceedings)  

Objective: Information about image quality of medical images is important for imaging system assessment in order to promote the development and manufacturing of state-of-the-art imaging systems. In this paper, we present a method for evaluating physical performance of digital medical imaging systems using mutual information which is a concept from information theory. To validate the proposed method, computer simulations were performed, followed by measuring and comparing the performance of two digital imaging systems. The results demonstrate the usefulness of the proposed method for evaluating physical quality of medical imaging systems. © 2011 IEEE.

DOI： 10.1109/BMEI.2011.6098601

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：SPIE-INT SOC OPTICAL ENGINEERING  

In this paper, we investigate the effect of the use of wavelet transform for image processing on radiation dose reduction in computed radiography (CR), by measuring various physical characteristics of the wavelet-transformed images. Moreover, we propose a wavelet-based method for offering a possibility to reduce radiation dose while maintaining a clinically acceptable image quality. The proposed method integrates the advantages of a previously proposed technique, i.e., sigmoid-type transfer curve for wavelet coefficient weighting adjustment technique, as well as a wavelet soft-thresholding technique. The former can improve contrast and spatial resolution of CR images, the latter is able to improve the performance of image noise. In the investigation of physical characteristics, modulation transfer function, noise power spectrum, and contrast-to-noise ratio of CR images processed by the proposed method and other different methods were measured and compared. Furthermore, visual evaluation was performed using Scheffe's pair comparison method. Experimental results showed that the proposed method could improve overall image quality as compared to other methods. Our visual evaluation showed that an approximately 40% reduction in exposure dose might be achieved in hip joint radiography by using the proposed method.

DOI： 10.1117/12.877740

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Language：English   Publishing type：Research paper (international conference proceedings)  

In this paper, we investigate the effect of the use of wavelet transform for image processing on radiation dose reduction in computed radiography (CR), by measuring various physical characteristics of the wavelet-transformed images. Moreover, we propose a wavelet-based method for offering a possibility to reduce radiation dose while maintaining a clinically acceptable image quality. The proposed method integrates the advantages of a previously proposed technique, i.e., sigmoid-type transfer curve for wavelet coefficient weighting adjustment technique, as well as a wavelet soft-thresholding technique. The former can improve contrast and spatial resolution of CR images, the latter is able to improve the performance of image noise. In the investigation of physical characteristics, modulation transfer function, noise power spectrum, and contrast-to-noise ratio of CR images processed by the proposed method and other different methods were measured and compared. Furthermore, visual evaluation was performed using Scheffe's pair comparison method. Experimental results showed that the proposed method could improve overall image quality as compared to other methods. Our visual evaluation showed that an approximately 40% reduction in exposure dose might be achieved in hip joint radiography by using the proposed method. © 2011 SPIE.

DOI： 10.1117/12.877740

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Authorship：Lead author,　Corresponding author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：WILEY  

Purpose: The objective was to develop and investigate an automated scoring scheme of the American College of Radiology (ACR) mammographic accreditation phantom (RMI 156, Middleton, WI) images.
Methods: The developed method consisted of background subtraction, determination of region of interest, classification of fiber and mass objects by Mahalanobis distance, detection of specks by template matching, and rule-based scoring. Fifty-one phantom images were collected from 51 facilities for this study (one facility provided one image). A medical physicist and two radiologic technologists also scored the images. The human and computerized scores were compared.
Results: In terms of meeting the ACR's criteria, the accuracies of the developed method for computerized evaluation of fiber, mass, and speck were 90%, 80%, and 98%, respectively. Contingency table analysis revealed significant association between observer and computer scores for microcalcifications (p &lt; 5%) but not for masses and fibers.
Conclusions: The developed method may achieve a stable assessment of visibility for test objects in mammographic accreditation phantom image in whether the phantom image meets the ACR's criteria in the evaluation test, although there is room left for improvement in the approach for fiber and mass objects. (C) 2010 American Association of Physicists in Medicine. [DOI: 10.1118/1.3516238]

DOI： 10.1118/1.3516238

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：The Japanese Society of Medical Imaging Technology  

In this report, we present an image evaluation method in which mutual information (MI) is employed as a metric for selecting the optimal wavelet basis function to be used in denoising planar nuclear images, with the objective of improving image quality. The higher the MI value, the better the image quality. We initially selected eight different wavelet basis functions for investigation in the present study. Subsequently, wavelet transforms were applied to planar images for denoising by employing the universal soft-thresholding method. Finally, the MI values of the wavelet-transformed images were computed for comparison. In this study, a computer-generated 2-D grid-pattern image and phantom images produced using a standard inkjet printer served as the original images. The results for the simulation and phantom images showed the same trend of ranking in terms of MI. The images processed by dmey wavelet showed the highest MI values. To validate the usefulness of the proposed method, the standard deviation rate and edge slope ratio of the processed images were calculated and compared. The results showed that the MI value can serve as an effective criterion for selecting the optimal wavelet basis function for image denoising. The results also showed that, of the eight wavelet basis functions investigated, dmey wavelet is the optimal basis function for denoising low-contrast planar images.

DOI： 10.11409/mit.28.371

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：LIPPINCOTT WILLIAMS & WILKINS  

Objective: The purpose of this study was to evaluate the usefulness of z-score mapping method on neuroradiologists&apos; performance in quantification of the extent of hypoattenuation regions of hyperacute stroke on unenhanced computed tomographic (CT) images by using the Alberta Stroke Programme Early CT Score system.
Methods: Twenty-one patients with infarction (&lt;3 hours) were retrospectively selected. Five neuroradiologists interpreted CT images first without and then with z-score maps by using the Alberta Stroke Programme Early CT Score system. Their performances in the quantification of the extent of hypoattenuation were compared.
Results: Average accuracies for the quantification without and with the z-score maps were 82.6% and 86.6%, respectively (P &lt; 0.0001). The average area under the receiver operating characteristic curve for detection of focal hypoattenuation significantly increased from 0.883 to 0.925 (P = 0.01) by use of z-score maps.
Conclusions: The use of z-score mapping method has the potential to help neuroradiologists quantify the extent of hypoattenuation regions of hyperacute stroke on unenhanced CT images.

DOI： 10.1097/RCT.0b013e3181e66473

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Language：Japanese   Publisher：日本医用画像工学会  

核医学画像のノイズを低減するためには、収集カウントを増加させる方法や画像データにフィルタリングを施す方法などがある。本研究では、後者に属するwavelet変換によるノイズ低減の手法に着目する。最初に既存のwavelet基底関数を8種類、候補として選択する。次に原画像に対しuniversalしきい値法を用いてwavelet縮退によるノイズ低減を施す。最後にwavelet逆変換後の画像の関心領域における相互情報量(mutual information:MI)を計算する。そしてMIを画質の単一評価指標として用い、8種類のwavelet基底関数で得た画像間の比較評価を行う。さらに、MI値による評価結果の妥当性を検証するために、画像の標準偏差率と画像のエッジ傾斜比を求め、これらの指標間の比較も行う。実験に用いる画像は、コンピュータ上で作成する2次元grid pattern像とインクジェットプリンタにより作成する面線源ファントム像である。これらの実験結果から、MIにより適切なwavelet基底関数の選択ができることを示す。(著者抄録)

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Language：Japanese   Publishing type：Research paper (bulletin of university, research institution)  

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Language：Japanese   Publisher：一般社団法人電子情報通信学会  

In this paper, we investigated the effect of the use of wavelet transform on dose reduction in computed radiography(CR). The physical properties of the processed CR images were measured using the modulation transfer function(MTF), noise power spectrum(NPS), contrast-to-noise ratio, and peak signal-to-noise ratio. Furthermore, visual evaluation was performed by Scheffe&#039;s pair comparison method. Experimental results showed that sigmoid-type transfer curves for wavelet coefficient weighting adjustment could improve the MTF, and three soft-threshold methods could improve the NPS at all spatial frequency ranges. Moreover, our visual evaluation showed that an approximately 40% reduction in exposure dose might be achieved with the sigmoid-type in hip joint radiography.

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ELSEVIER SCIENCE INC  

Rationale and Objectives: The purpose of this study was to develop a z-score mapping method on the basis of a voxel-by-voxel analysis to visualize hypoattenuation areas of hyperacute stroke on unenhanced computed tomographic (CT) images.
Materials and Methods: The algorithm of the developed method consisted of five main steps: anatomic standardization, the construction of a normal reference database, calculation of the z scores, the elimination of false-positive areas, and the extraction of hypoattenuation areas. The obtained z-score map was then superimposed on the original CT images for identifying hypoattenuation areas of hyperacute stroke on the unenhanced CT images. The method was applied to 21 patients with infarctions of the middle cerebral artery territory &lt;3 hours after symptom onset. The performance of the method was evaluated using receiver-operating characteristic analysis.
Results: Hypoattenuation regions could be significantly distinguished from normal regions by z-score values (P&lt;.0001). The area under the receiver-operating characteristic curve for distinction between 68 hypoattenuation regions and 142 normal regions was 0.834.
Conclusions: The developed method has the potential to accurately indicate high-signal intensity areas corresponding to hypoattenuation areas on CT images in the hyperacute stage of stroke.

DOI： 10.1016/j.acra.2009.07.011

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IOP PUBLISHING LTD  

In this paper, we investigated the effect of the use of wavelet transform on dose reduction in computed radiography (CR). The physical properties of the processed CR images were measured using the modulation transfer function (MTF), noise power spectrum (NPS), contrast-to-noise ratio, and peak signal-to-noise ratio. Furthermore, visual evaluation was performed by Scheffe's pair comparison method. Experimental results showed that sigmoid-type transfer curves for wavelet coefficient weighting adjustment could improve the MTF, and three soft-threshold methods could improve the NPS at all spatial frequency ranges. Moreover, our visual evaluation showed that an approximately 40% reduction in exposure dose might be achieved with the sigmoid-type transfer curve in hip joint radiography.

DOI： 10.1088/1742-6596/238/1/012055

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Language：Japanese   Publisher：MEDICAL IMAGING AND INFORMATION SCIENCES  

In this paper, a novel application of computer-aided diagnosis (CAD) system, namely portable CAD, was proposed. As a preliminary study, we investigated differences of feature values of nodules calculated by a CAD algorithm, between original chest radiograph and camera image taken by a digital camera. Sixty cases of chest radiographs were used in the study. These radiographs were initially displayed on the monitor, and then taken by the digital camera. Then, the CAD scheme was applied to the obtained camera images. In the CAD scheme, detection of nodule candidates was performed by using matched and ring filters. Two features, area and circularity, were calculated from nodule candidate regions in radiographs and camera images, and were compared respectively. In conclusion, a close correlation between the features calculated from radiographs and camera images was verified.

DOI： 10.11318/mii.27.29

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Japanese Society of Radiological Technology  

Joint photographic experts group(JPEG)and JPEG2000 are widely used as image compression algorithms in medical image database systems. Compressed images have been mainly evaluated by visual assessment on acceptable compression levels in clinical studies. However, to the best of our knowledge, little work has been done to clarify image properties based on physical analysis. In this work, investigations were made to clarify image properties based on physical analysis and to discuss the major causes of degradation related to compression ratios. The physical properties of JPEG2000-compressed and JPEG-compressed images in computed radiography(CR)were compared by measuring the characteristic curve, modulation transfer function(MTF), noise power spectrum(NPS), peak signal-to-noise ratio(PSNR), contrast-to-noise ratio(CNR), and noise equivalent quanta(NEQ). In the MTF measurement, the MTFs of JPEG at high compression ratio showed pronounced degradation at all frequencies. The NPS values of JPEG2000 tend to decrease considerably compared to that of the JPEG at all frequencies with the increase of compression ratio. Furthermore, JPEG2000 images showed higher PSNR, CNR, and NEQ values than JPEG images in the same compression ratio. In these signal-to-noise ratio measurements, good reproducibility of JPEG2000 images was achieved. Overall, JPEG2000 compressed images were far superior to JPEG compressed images. In the physical properties measured, these physical analyses are useful to comprehend physical properties for each irreversible compressed image related to compression ratios in CR.

DOI： 10.6009/jjrt.65.1618

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Other Link： https://jlc.jst.go.jp/DN/JALC/00346507171?from=CiNii

Language：Japanese   Publishing type：Research paper (scientific journal)  

DOI： 10.6009/jjrt.65.1313

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：I S & T - SOC IMAGING SCIENCE TECHNOLOGY  

We describe an information-theoretic method for quantifying overall image quality in terms of mutual information (MI). MI is used to express the amount of information that an output image contains about an input object. The more the MI value provides, the better the image quality is. Therefore, the overall quality of an image can be quantitatively evaluated by measuring MI. We demonstrated by way of image simulation that MI increases with increasing contrast and decreases with the increase of noise and blur. We investigated the utility of this method by applying it to evaluate the performance of four imaging plate detectors. We also compared evaluation results in terms of MI against those in terms of the detective quantum efficiency conventionally used for characterizing the efficiency performance of imaging systems. Our results demonstrate that the proposed method is simple to implement and has potential usefulness for evaluation of overall image quality. (C) 2009 SPIE and IS&T. [DOI: 10.1117/1.3206967]

DOI： 10.1117/1.3206967

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Language：Japanese   Publishing type：Research paper (bulletin of university, research institution)   Publisher：Niigata University  

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Other Link： http://search.jamas.or.jp/link/ui/2009151083

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This paper presents a computerized scheme to assist MRI operators in accurate and rapid determination of sagittal sections for MRI exam of cervical spinal cord. The algorithm of the proposed scheme consisted of 6 steps: (1) extraction of a cervical vertebra containing spinal cord from an axial localizer image
(2) extraction of spinal cord with sagittal image from the extracted vertebra
(3) selection of a series of coronal localizer images corresponding to various, involved portions of the extracted spinal cord with sagittal image
(4) generation of a composite coronal-plane image from the obtained coronal images
(5) extraction of spinal cord from the obtained composite image
(6) determination of oblique sagittal sections from the detected location and gradient of the extracted spinal cord. Cervical spine images obtained from 25 healthy volunteers were used for the study. A perceptual evaluation was performed by five experienced MRI operators. Good agreement between the automated and manual determinations was achieved. By use of the proposed scheme, average execution time was reduced from 39 seconds/case to 1 second/case. The results demonstrate that the proposed scheme can assist MRI operators in performing cervical spinal cord MRI exam accurately and rapidly. © 2009 Copyright SPIE - The International Society for Optical Engineering.

DOI： 10.1117/12.811082

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IMEKO  

Information on physical image quality of medical images is important for imaging system assessment in order to promote and stimulate the development of state-of-the-art imaging systems. In this paper, we present a method for measuring physical performance of medical imaging systems. In this method, mutual information (MI) which is a concept from information theory was used to measure combined properties of image noise and resolution of an imaging system. In our study, the MI was used as a measure to express the amount of information that an output image contains about an input object. The more the MI value provides, the better the image quality is. To validate the proposed method, computer simulations were first performed to investigate the effects of noise and resolution degradation on the MI. Then experiments were conducted to measure the physical performance of an imaging plate which was used as an image detector. Our simulation and experimental results confirmed that the combined effect of deteriorated blur and noise on the images can be measured and analyzed using the MI metric. The results demonstrate the potential usefulness of the proposed method for measuring physical quality of medical imaging systems.

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：MEDICAL IMAGING AND INFORMATION SCIENCES  

Manual determination of an oblique sagittal imaging plane with high accuracy in lumbar spine magnetic resonance imaging(MRI)needs time, experience and expertise. In this paper we present a simple and fast setting system for assisting MRI operators in their routine work to automatically and accurately determine oblique sagittal imaging plane in lumbar spine MRI. The algorithm of the presented method consists of three major steps:(1)extraction of torso region from coronal localizer image by use of histogram analysis,(2)extraction of lumbar vertebra and spinal canal regions by use of minimization and maximization filters as well as density accumulation analysis, and(3)determination of the desired position and angle of sagittal imaging plane using Hough transform. In order to evaluate the performance of our proposed method, positions and angles of the sagittal imaging planes determined by the presented method were evaluated by five radiological technologists. Thirty healthy volunteers participated in this study. All the 5 observers confirmed that the automatically determined imaging planes of all the 30 cases were acceptable for subsequent imaging procedures.

DOI： 10.11318/mii.25.54

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Authorship：Lead author   Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：MEDICAL IMAGING AND INFORMATION SCIENCES  

Pre-processing is important for digital medical images because it can contribute to the improvement of diagnostic accuracy with medical images and computer-aided diagnosis. In this paper, a novel sigmoid-type transfer curve for wavelet coefficient weighting adjustment was proposed to improve contrast of medical images. The proposed method was applied to chest radiographs, mammograms and chest CT images, and then its performance was quantitatively evaluated with contrast improvement ratio. As a result, contrasts of all applied images were obviously improved. Compared with the conventional exponential-type transfer curve, the proposed sigmoid-type transfer curve was more effective with a statistical significance(<i>p</i><0.05).

DOI： 10.11318/mii.25.48

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：SPRINGER  

This paper presents a simple and straightforward method for synthetically evaluating digital radiographic images by a single parameter in terms of transmitted information (TI). The features of our proposed method are (1) simplicity of computation, (2) simplicity of experimentation, and (3) combined assessment of image noise and resolution (blur). Two acrylic step wedges with 0-1-2-3-4-5 and 0-2-4-6-8-10 mm in thickness were used as phantoms for experiments. In the present study, three experiments were conducted. First, to investigate the relation between the value of TI and image noise, various radiation doses by changing exposure time were employed. Second, we examined the relation between the value of TI and image blurring by shifting the phantoms away from the center of the X-ray beam area toward the cathode end when imaging was performed. Third, we analyzed the combined effect of deteriorated blur and noise on the images by employing three smoothing filters. Experimental results show that the amount of TI is closely related to both image noise and image blurring. The results demonstrate the usefulness of our method for evaluation of physical image quality in medical imaging.

DOI： 10.1007/s10278-007-9044-5

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Authorship：Lead author,　Corresponding author   Language：English   Publishing type：Research paper (scientific journal)  

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Language：Japanese   Publishing type：Research paper (scientific journal)  

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Language：Japanese   Publishing type：Research paper (bulletin of university, research institution)   Publisher：Niigata University  

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Other Link： http://search.jamas.or.jp/link/ui/2008264517

Language：English   Publishing type：Research paper (bulletin of university, research institution)   Publisher：Niigata University  

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Other Link： http://search.jamas.or.jp/link/ui/2008264516

Publishing type：Research paper (scientific journal)  

DOI： 10.6009/jjrt.64.881

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ROYAL SOC MEDICINE PRESS LTD  

Background: Much attention has been directed toward identifying early signs of cerebral ischemia on computed tomography (CT) images. Hypoattenuation of ischemic brain parenchyma has been found to be the most frequent early sign.
Purpose: To evaluate the effect of a previously proposed adaptive smoothing filter for improving detection of parenchymal hypoattenuation of acute ischemic stroke on unenhanced CT images.
Material and Methods: Twenty-six patients with parenchymal hypoattenuation and 49 control subjects without hypoattenuation were retrospectively selected in this study. The adaptive partial median filter (APMF) designed for improving detectability of hypoattenuation areas on unenhanced CT images was applied. Seven radiologists, including four certified radiologists and three radiology residents, indicated their confidence level regarding the presence (or absence) of hypoattenuation on CT images, first without and then with the APMF processed images. Their performances without and with the APMF processed images were evaluated by receiver operating characteristic (ROC) analysis.
Results: The mean areas under the ROC curves (AUC) for all observers increased from 0.875 to 0.929 (P=0.002) when the radiologists observed with the APMF processed images. The mean sensitivity in the detection of hypoattenuation significantly improved, from 69% (126 of 182 observations) to 89% (151 of 182 observations), when employing the APMF (P=0.012). The specificity, however, was unaffected by the APMF (P=0.41).
Conclusion: The APMF has the potential to improve the detection of parenchymal hypoattenuation of acute ischemic stroke on unenhanced CT images.

DOI： 10.1080/02841850802126570

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：SPIE-INT SOC OPTICAL ENGINEERING  

This paper presents an information-entropy based metric for combined evaluation of resolution and noise properties of radiological images. The metric is expressed by the amount of transmitted information (TI). It is a measure of how much information that one image contains about an object or-an input. Merits of the proposed method are its simplicity of computation and the experimented setup. A computer-simulated step wedge was used for simulation study on the relationship of TI and the degree of blur as well as the noise. Three acrylic step wedges were also manufactured and used as test sample objects for experiments. Two imaging plates for computed radiography were employed as information detectors to record X-ray intensifies. We investigated the effects of noise and resolution degradation on the amount of TI by varying exposure levels. Simulation and experimental results show that the TI value varies when the noise level or the degree of blur is changed. To validate the reasoning and usefulness of the proposed metric, we also calculated and compared the modulation transfer functions and noise power spectra for the employed imaging plates. Results show that the TI has close correlation with both image noise and image blurring, and it may offer the potential to become a simple and generally applicable measure for quality evaluation of medical images.

DOI： 10.1117/12.768324

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Language：English   Publishing type：Research paper (international conference proceedings)  

This paper presents an information-entropy based metric for combined evaluation of resolution and noise properties of radiological images. The metric is expressed by the amount of transmitted information (TI). It is a measure of how much information that one image contains about an object or an input. Merits of the proposed method are its simplicity of computation and the experimented setup. A computer-simulated step wedge was used for simulation study on the relationship of TI and the degree of blur as well as the noise. Three acrylic step wedges were also manufactured and used as test sample objects for experiments. Two imaging plates for computed radiography were employed as information detectors to record X-ray intensities. We investigated the effects of noise and resolution degradation on the amount of TI by varying exposure levels. Simulation and experimental results show that the TI value varies when the noise level or the degree of blur is changed. To validate the reasoning and usefulness of the proposed metric, we also calculated and compared the modulation transfer functions and noise power spectra for the employed imaging plates. Results show that the TI has close correlation with both image noise and image blurring, and it may offer the potential to become a simple and generally applicable measure for quality evaluation of medical images.

DOI： 10.1117/12.768324

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Authorship：Lead author,　Corresponding author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：SPRINGER HEIDELBERG  

Purpose: Detection of early CT signs of infarct in non-enhanced CT image is mandatory in patients with acute ischemic stroke. Loss of the gray-white matter interface at the lentiform nucleus or the insular ribbon has been an important early CT sign of acute cerebral infarction, which affects decisions on thrombolytic therapy. However, its detection is difficult, since the principal early CT sign is subtle hypoattenuation. An image processing method to reduce local noise with edges preserved was developed to improve infarct detection.
Rationale: An adaptive partial median filter (APMF) was selected for this application, since the APMF can markedly improve the visibility of the normal gray-white matter interface. APMF should enhance the conspicuity of gray-white matter interface changes due to hypoattenuation that accompanies cerebral infarction.
Method: In a criterion referenced performance study using simulated CT images with gray-white matter interfaces, a total of 14 conventional smoothing filters were also used for comparison to validate the usefulness of the proposed APMF. The APMF indicated the highest performance among the compared methods. Then, observer performance study by receiver operator characteristic (ROC) analysis was performed with 4 radiologist observers using a database with 18 abnormal and 33 normal head CT images.
Results: The average A(z) values of ROC curves for all radiologists increased from 0.876 without the APMF images to 0.926 with the APMF images, and this difference was statistically significant (P = 0.04).
Conclusions: The results from the two observer performance studies demonstrated that APMF has significant potential to improve the diagnosis of acute cerebral infarction using non-enhanced CT images.

DOI： 10.1007/s11548-007-0123-3

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Japanese Society of Radiological Technology (JSRT)  

This paper describes an approach to automatically detect the parenchymal hypoattenuation of hyperacute stroke in nonenhanced computed tomography (CT) images. This technique is based on a comparison between the CT values histograms of right and left brains. A subtraction curve that was regarded as an output value was calculated by subtracting the right-hemispherical histogram from the left-hemispherical histogram obtained from one of the region-of-interest (ROI) sets on an image. The output value was used to assess whether hypoattenuation exists on CT images with a threshold value. If judged abnormal, a rectangular region including a whole or partial hypoattenuation area was detected from the ROI. Twenty-six cases with hypoattenuation and 30 cases without hypoattenuation were included in this study. As a result of our experiments, the sensitivity of this method in detecting hypoattenuation was found to be 92%, with approximately 0.16 false-positive per image. Our preliminary experimental results indicated that the proposed technique can be used for the automated detection of parenchymal hypoattenuation of hyperacute stroke on nonenhanced CT images. [Article in Japanese]

DOI： 10.6009/jjrt.63.835

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Language：English   Publishing type：Research paper (scientific journal)  

Purpose. The aim of this study was to evaluate the performance of a novel noise reduction filter for improving the visibility of early computed tomography (CT) signs of hyperacute stroke on nonenhanced CT images. Material and methods. Fourteen patients with a middle cerebral artery occlusion within 4.5 h after onset were evaluated. The signal-to-noise ratio (SNR) of the processed images with the noise reduction filter and that of original images were measured. Two neuroradiologists visually rated all the processed and original images on the visibility of normal and abnormal gray-white matter interfaces. Results. The SNR value of the processed images was approximately eight times as high as that of the original images, and a 87% reduction of noise was achieved using this technique. For the visual assessment, the results showed that the visibility of normal gray-white matter interface and that of the loss of the gray-white matter interface were significantly improved using the proposed method (P &lt
0.05). Conclusion. The noise reduction filter proposed in the present study has the potential to improve the visibility of early CT signs of hyperacute stroke on nonenhanced CT images. © 2007 Japan Radiological Society.

DOI： 10.1007/s11604-007-0129-3

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Authorship：Lead author   Language：Japanese   Publishing type：Research paper (scientific journal)  

DOI： 10.6009/jjrt.63.341

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Authorship：Lead author,　Corresponding author   Language：Japanese   Publishing type：Research paper (scientific journal)  

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：The Institute of Electronics, Information and Communication Engineers  

Computed tomography (CT) is an important modality for diagnosis of hyper-acute stroke. In this study, a novel adaptive partial median filter (APMF) that aimed to improve detectability of hyper-acute stroke on non-enhanced brain CT images was proposed. The APMF can reduce noise components while preserving signal components. Adequate parameters of APMF for detectability improvement of hyper-acute stroke were determined by simulation, and then, APMF were applied to clinical images. The results showed that the detectability of hyper-acute stroke were much improved.

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：The Institute of Electronics, Information and Communication Engineers  

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Other Link： http://hdl.handle.net/10191/8168

Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Japanese Society of Radiological Technology (JSRT)  

DOI： 10.6009/jjrt.62.447

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Other Link： http://hdl.handle.net/10191/4863

Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：The Institute of Electronics, Information and Communication Engineers  

We have been developing a computer-aided diagnosis (CAD) system for detecting lung nodules isolated and touched lung wall in chest X-ray CT images. In this paper, a new detection method was proposed by using the higher-order autocorrelation features and the Lung Wall Template Matching (LWTM). We investigate the performance of this method by the simulation study. As a result, we achieved the sensitivity of 86.3% (63/73) with 10.9 false positives (FPs) per case in 35 clinical cases.

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：SPIE-INT SOC OPTICAL ENGINEERING  

Detection of early infarct signs on non-enhanced CT is mandatory in patients with acute ischemic stroke. We present a method for improving the detectability of early infarct signs of acute ischemic stroke. This approach is considered as the first step for computer-aided diagnosis in acute ischemic stroke. Obscuration of the gray-white matter interface at the lentiform nucleus or the insular ribbon has been an important early infarct sign, which affects decisions on thrombolytic therapy. However, its detection is difficult, since the early infarct sign is subtle hypoattenuation. In order to improve the detectability of the early infarct sign, an image processing being able to reduce local noise with edges preserved is desirable. To cope with this issue, we devised an adaptive partial smoothing filter (APSF). Because the APSF can markedly improve the visibility of the normal gray-white matter interface, the detection of conspicuity of obscuration of gray-white matter interface due to hypoattenuation could be increased. The APSF is a specifically designed filter used to perform local smoothing using a variable filter size determined by the distribution of pixel values of edges in the region of interest. By adjusting four parameters of the APSF, an optimal condition for image enhancement can be obtained. In order to determine a major one of the parameters, preliminary simulation was performed by using composite images simulated the gray-white matter. The APSF based on preliminary simulation was applied to several clinical CT scans in hyperacute stroke patients. The results showed that the detectability of early infarct signs is much improved.

DOI： 10.1117/12.654242

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：SPIE-INT SOC OPTICAL ENGINEERING  

In this paper we describe a method for assisting radiological technologists in their routine work to automatically determine the imaging plane in lumbar MRI. The method is first to recognize the spinal cord and the intervertebral disk (ID) from the lumbar vertebra 3-plane localizer image, and then the imaging plane is automatically determined according to the recognition results. To determine the imaging plane, the spinal cord and the ID are automatically recognized from the lumbar vertebra 3-plane localizer image with a series of image processing techniques. The proposed method consists of three major steps. First, after removing the air and fat regions from the 3-plane localizer image by use of histogram analysis, the rachis region is specified with Sobel edge detection filter. Second, the spinal cord and the ID were respectively extracted from the specified rachis region making use of global thresholding and the line detection filter. Finally, the imaging plane is determined by finding the straight line between the spinal cord and the ID with the Hough transform. Image data of 10 healthy volunteers were used for investigation. To validate the usefulness of our proposed method, manual determination of the imaging plane was also conducted by five experienced radiological technologists. Our experimental results showed that the concordance rate between the manual setting and automatic determination reached to 90%. Moreover, a remarkable reduction in execution time for imaging-plane determination was also achieved.

DOI： 10.1117/12.652908

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Detection of early infarct signs on non-enhanced CT is mandatory in patients with acute ischemic stroke. We present a method for improving the detectability of early infarct signs of acute ischemic stroke. This approach is considered as the first step for computer-aided diagnosis in acute ischemic stroke. Obscuration of the gray-white matter interface at the lentiform nucleus or the insular ribbon has been an important early infarct sign, which affects decisions on thrombolytic therapy. However, its detection is difficult, since the early infarct sign is subtle hypoattenuation. In order to improve the detectability of the early infarct sign, an image processing being able to reduce local noise with edges preserved is desirable. To cope with this issue, we devised an adaptive partial smoothing filter (APSF). Because the APSF can markedly improve the visibility of the normal gray-white matter interface, the detection of conspicuity of obscuration of gray-white matter interface due to hypoattenuation could be increased. The APSF is a specifically designed filter used to perform local smoothing using a variable filter size determined by the distribution of pixel values of edges in the region of interest. By adjusting four parameters of the APSF, an optimal condition for image enhancement can be obtained. In order to determine a major one of the parameters, preliminary simulation was performed by using composite images simulated the gray-white matter. The APSF based on preliminary simulation was applied to several clinical CT scans in hyperacute stroke patients. The results showed that the detectability of early infarct signs is much improved.

DOI： 10.1117/12.654242

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Springer Verlag  

DOI： 10.1007/s11548-006-0031-y

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In this paper we describe a method for assisting radiological technologists in their routine work to automatically determine the imaging plane in lumbar MRI. The method is first to recognize the spinal cord and the intervertebral disk (ID) from the lumbar vertebra 3-plane localizer image, and then the imaging plane is automatically determined according to the recognition results. To determine the imaging plane, the spinal cord and the ID are automatically recognized from the lumbar vertebra 3-plane localizer image with a series of image processing techniques. The proposed method consists of three major steps. First, after removing the air and fat regions from the 3-plane localizer image by use of histogram analysis, the rachis region is specified with Sobel edge detection filter. Second, the spinal cord and the ID were respectively extracted from the specified rachis region making use of global thresholding and the line detection filter. Finally, the imaging plane is determined by finding the straight line between the spinal cord and the ID with the Hough transform. Image data of 10 healthy volunteers were used for investigation. To validate the usefulness of our proposed method, manual determination of the imaging plane was also conducted by five experienced radiological technologists. Our experimental results showed that the concordance rate between the manual setting and automatic determination reached to 90%. Moreover, a remarkable reduction in execution time for imaging-plane determination was also achieved.

DOI： 10.1117/12.652908

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Japanese Society of Radiological Technology  

Detection of early infarct signs on nonenhanced CT is mandatory in patients with acute ischemic stroke. Loss of the gray-white matter interface at the lentiform nucleus or the insular ribbon has been an important early infarct sign, which affects decisions on thrombolytic therapy. However, its detection is difficult, since early infarct sign is of subtle hypoattenuation. To improve the detectability of early infarct sign, image processing that could reduce local noise while preserving edges is desirable. To examine this issue, we devised an adaptive partial smoothing filter (APSF). Since the APSF markedly improves visibility of the normal gray-white matter interface, loss of the gray-white matter interface due to hypoattenuation could be more easily detected. The APSF was applied to clinical CT images in hyperacute stroke patients. Our preliminary results showed that the visibility and detectability of early infarct signs was much improved. To validate the usefulness of the proposed method, two commonly used smoothing filters were also employed for comparison. The results demonstrated the superiority of the APSF. Our proposed APSF can improve the visibility of the gray-white matter interface, thereby enhancing the detectability of early infarct signs.

DOI： 10.6009/jjrt.KJ00004010674

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Other Link： http://hdl.handle.net/10191/4862

Authorship：Lead author   Language：Japanese   Publishing type：Research paper (scientific journal)  

DOI： 10.11409/mit.23.239

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Japanese Society of Radiological Technology  

This paper presents an improved adaptive-neighborhood-contrast-enhancement (ANCE) method for the improvement of medical image quality. The ANCE method consists of computing the local contrast around each pixel using a variable neighborhood whose size depends on the statistical properties around the given pixel. The obtained contrast image is then transformed into a new contrast image using a contrast enhancement function. Finally, a contrast-enhanced image is obtained by applying inverse contrast transform to the previous step. This technique provides the advantages of enhancing or preserving image contrast while suppressing noise. However, it does have a drawback. The performance of the ANCE method largely depends on how to determine the parameters used in the processing steps. The present study proposes a novel method for optimal and automatic determination of several parameters using entropy. To quantitatively compare the performance of the proposed method with that of the ANCE method, computer-simulated images are generated. The output-to-input SNR level and the mean squared error are used as comparison criteria. Results demonstrated the superiority of the proposed method. Moreover, we have applied our new algorithm to echocardiograms and mammograms. Our results showed that the proposed method has the potential to become useful for improving the image quality of medical images.

DOI： 10.6009/jjrt.KJ00003326665

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Other Link： http://hdl.handle.net/10191/4861

Language：Japanese   Publishing type：Research paper (scientific journal)  

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

We present an adaptive smoothing filter aiming to improve the visibility and detectability of the obscuration of the lentiform, nucleus, which is one of the early signs of acute cerebral artery infraction, in CT brain images. The proposed method is able to enhance image data by removing noise without significantly blurring the structures in the images. This method is tested both on computer-simulated image data and on clinical CT brain images. Moreover, a comparison of the proposed method to two commonly used techniques is made. Preliminary results demonstrate the superiority of the proposed method and its usefulness for detecting the obscuration of the lentiform nucleus, which could not be detected previously without using the proposed method.

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Language：Japanese   Publisher：公益社団法人 日本放射線技術学会  

DOI： 10.6009/jjrt.KJ00004028181

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：I S & T - SOC IMAGING SCIENCE TECHNOLOGY  

In this paper we present a genetic-algorithm-based fuzzy-logic approach for computer-aided diagnosis scheme in medical imaging. The scheme is applied to discriminate myocardial heart disease from echocardiographic images and to detect and classify clustered microcalcifications from mammograms. Unlike the conventional types of membership functions such as trapezoid, triangle, S curve, and singleton used in fuzzy reasoning, Gaussian-distributed fuzzy membership functions (GDMFs) are employed in the present study. The GDMFs are initially generated using various texture-based features obtained from reference images. Subsequently the shapes of GDMFs are optimized by a genetic-algorithm learning process. After optimization, the classifier is used for disease discrimination. The results of our experiments are very promising. We achieve an average accuracy of 96% for myocardial heart disease and accuracy of 88.5% at 100% sensitivity level for micro-calcification on mammograms. The results demonstrated that our proposed genetic-algorithm-based fuzzy-logic approach is an effective method for computer-aided diagnosis in disease classification. 2004, SPIE and IST.

DOI： 10.1117/1.1786607

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：(公社)日本医学物理学会  

多列Multi-slice CTの開発に伴い,これまでのline spread function(LSF)やslice sensitivity profile(SSP)を用いた1次元での検討から,2次元や3次元に拡張しての検討が重要になるが,LSFやSSPとpoint spread function(PSF)の関係について詳細に論ずる報告はみあたらない.そこで,LSFおよびSSPとPSFの関係について理論的に考察し,シミュレーションを加えて,それらの関連を明らか場合,その系のPSF'(x,y,z)はLSSFx(X)とLSFy(Y)およびSSP(z)の積で表すことができ,PSF(x,y)はLSFx(X)とLSFy(Y)の積で表すことができた

DOI： 10.11323/jjmp2000.24.3_115

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Other Link： https://search.jamas.or.jp/index.php?module=Default&action=Link&pub_year=2004&ichushi_jid=J03418&link_issn=&doc_id=20041201260002&doc_link_id=10014056519&url=https%3A%2F%2Fci.nii.ac.jp%2Fnaid%2F10014056519&type=CiNii&icon=https%3A%2F%2Fjk04.jamas.or.jp%2Ficon%2F00003_1.gif

Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Japanese Society of Radiological Technology  

We propose an approach for automated detection of cerebral vessels from head CT angiographic images. This approach contains two major features. First, instead of using the well-known image-processing techniques such as thresholding and labeling, a novel Laplacian-like filter is developed and employed in the region of interest in an image to be processed. Second, not only is the axial-view image reconstructed from head CT angiographic images used, but, in addition, the sagittal-and coronal-view images are reconstructed and used. By applying these major features in the process of detection of brain vessels, more accurate results can be achieved. To validate the effectiveness of the proposed method, we applied the method to three clinical cases, all of which were head CT angiograms. Our preliminary results showed that the proposed method has the potential to automatically detect cerebral vessels in head CT angiograms with acceptable accuracy.

DOI： 10.6009/jjrt.KJ00003174600

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Other Link： http://search.jamas.or.jp/link/ui/2005025516

Language：Japanese   Publishing type：Research paper (conference, symposium, etc.)  

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Authorship：Lead author   Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：MEDICAL IMAGING AND INFORMATION SCIENCES  

The purpose of this study is to compare four CAD-algorithms under the same condition, and to verify the most effective algorithm for the classification of microcalcifications on mammogram. The four CAD-algorithms are BP-ANN, GA-ANN, FL and GA-FL. BP-ANN is a conventional artificial neural network with back-propagation learning. GA-ANN is an improved ANN based on genetic algorithm to determine the weighting coefficients at ANN. FL is a conventional fuzzy logic algorithm using gaussian-distributed membership functions. GA-FL is an improved FL based on genetic algorithm to optimize the membership functions. Comparison results are indicated by ROC curves. The Az values of the ROC curves for BP-ANN, GA-ANN, FL and GA-FL were 0.86, 0.80, 0.89 and 0.95, respectively. When sensitivity of each algorithm was 100%, specificities of BP-ANN, GA-ANN, FL and GA-FL were 69%, 54%, 31% and 77%, respectively. Therefore, these results show the effectiveness of GA-FL algorithm. GA-FL has a potential to become useful CAD algorithm to classify microcalcifications on mammogram.

DOI： 10.11318/mii.21.122

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：SPRINGER-VERLAG BERLIN  

This paper presents an improved adaptive neighborhood contrast enhancement (ANCE) method for improvement of medical image quality. The ANCE method provides the advantages of enhancing or preserving image contrast while suppressing noise. However, it has a drawback. The performance of the ANCE method largely depends on how to determine the parameters used in the processing steps. The present study proposes a novel method for optimal and automatic determination of threshold-value and neighborhood-size parameters using entropy. To quantitatively compare the performance of the proposed method with that of the ANCE method, computer-simulated images are generated. The output-to-input SNR ratio and the mean squared error are used as comparison criteria. Results demonstrate the superiority of the proposed method. Moreover, we have applied our new algorithm to echocardiograms. Our results show that the proposed method has the potential to become useful for improvement of image quality of medical images.

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：SPIE-INT SOC OPTICAL ENGINEERING  

We previously developed a scheme to automatically detect pulmonary nodules on CT images, as a part of computer-aided diagnosis (CAD) system. The proposed method consisted of two template-matching approaches based on simple models that simulate real nodules. One was a new template-matching technique based on a genetic algorithm (GA) template matching (GATM) for detecting nodules within the lung area. The other one was a conventional template matching along the lung wall [lung wall template matching (LWTM)] for detecting nodules on the lung wall. After the two template matchings, thirteen feature values were calculated and used for eliminating false positives. Twenty clinical cases involving a total of 557 sectional images were applied; 71 nodules out of 98 were correctly detected with the number of false positives at approximately 30.8/case by applying two template matchings (GATM and LWTM) and elimination process of false positives. In this study, five features were newly added, and threshold-values of our previous features were reconsidered for further eliminating false positives. As the result, the number of false positives was decreased to 5.5/case without elimination of true positives.

DOI： 10.1117/12.536162

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：SPIE-INT SOC OPTICAL ENGINEERING  

The purpose of this study is to develop a computerized scheme for the discrimination between benign and malignant clustered microcalcifications that would aid radiologists in interpreting mammograms. In our scheme, microcalcifications in regions of interest (ROIs) are detected by using morphological filter. Then, four feature values including the total number, mean area, mean circularity and mean minimum distance of microcalcifications are calculated for classification. Gaussian-distributed membership functions used for fuzzy logic are determined from means and standard deviations of these feature values. Finally, fuzzy logic using the genetic-algorithm for optimization of membership functions is employed to classify clustered microcalcifications in unknown ROI. Our scheme was applied to twenty mammographic images with microcalcifications in the Mammographic Image Analysis Society database, containing thirteen benign and twelve malignant ROIs. Of the images ten each benign and malignant ROIs were used for training in fuzzy logic. The remaining five images were classified as benign or malignant cases by fuzzy logic. All sets of their combinations were employed to obtain the result. As the results, the average accuracy was approximately 88% (sensitivity: 100%, specificity: 77%), and Az value of ROC curve was 0.95.

DOI： 10.1117/12.536274

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Language：Japanese   Publisher：公益社団法人 日本放射線技術学会  

DOI： 10.6009/jjrt.KJ00003174512

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：新潟大学医学部保健学科  

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Other Link： http://search.jamas.or.jp/link/ui/2004194207

Authorship：Lead author   Language：Japanese   Publishing type：Research paper (scientific journal)  

DOI： 10.11239/jsmbe2002.41.105

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

An approach to,medical image enhancement is proposed. In this method, non-linear mapping functions are derived for projecting a set of discrete wavelet transform (DWT) coefficients to a new set of DWT coefficients. The mapped coefficients are then inverse wavelet transformed. Applications of the proposed method to the chest x-ray images and mammograms with subtle micro-calcifications are shown. To validate the effectiveness of the proposed method, we compared the results to those obtained by the fast Fourier transform (FFT) and the conventional wavelet-based (CWB) methods. Our preliminary results strongly suggest that the proposed method offers considerably improved enhancement capability over the FFT and CWB methods.

DOI： 10.1109/ICNNSP.2003.1281059

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Japanese Society of Radiological Technology  

The purpose of this study is to develop a technique to detect lacunar infarct regions automatically in brain MR images. Our detection method is based on the definition of lacunar infarcts. After inputted images were binarized, we used feature values such as area, circularities and the center of gravity of candidate regions to extract isolated lacunar infarct regions. We also developed and used a new filter to enhance the signals of lacunar infarcts adjacent to some high intensity regions. 10 cases involving 81 sectional images were applied to our experiment. As a result, the sensitivity was 100% with approximately 1.77 false-positives per image. Our results are promising on the first stage, although it remains to improve on problems that to eliminate false-positives and automatically establish threshold value.

DOI： 10.6009/jjrt.KJ00001364293

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Other Link： http://search.jamas.or.jp/link/ui/2002207001

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This paper presents a wavelet-based method for the edge enhancement of medical images. In the proposed method, a novel transfer function is introduced for weighting wavelet coefficients when multiresolution levels and absolute values of the wavelet coefficients are low and great, respectively, thereby resulting in edge enhancement. A Fourier transform method, a conventional wavelet-based method that used a simple transfer function, and our proposed method were compared. These methods were applied to two chest radiographic images. As a result, the proposed method could enhance the edges of the ribs, bronchus, and pulmonary vessels without a significant enhancement of noise in comparison with the Fourier transform and conventional methods. © 2002, Japanese Society for Medical and Biological Engineering. All rights reserved.

DOI： 10.11239/jsmbe1963.40.86

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：SCRIPTA TECHNICA-JOHN WILEY & SONS  

This paper describes a fuzzy-reasoning-based computer-aided diagnosis scheme for automated classification of cardiomyopathy from ultrasonic images. Unlike the conventional types of membership functions such as triangle and trapezoid, Gaussian-distributed membership functions (GDMFs) are employed in the present study. The GDMFs are initially generated using various texture-based features computed from gray-level co-occurrence matrices. Subsequently, the shapes of GDMFs are optimized by a genetic-algorithm learning process. After optimization, the classifier is used to discriminate two sets of echocardiographic images, namely, normal and abnormal cases, which were diagnosed in advance by a highly trained physician. We experimentally evaluate the performance of the proposed method against various methods reported in terms of sensitivity, specificity, and total accuracy. Our results show the promise of the proposed approach in discriminating cardiomyopathy. (C) 2002 Wiley Periodicals, Inc.

DOI： 10.1002/ecjc.10025

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

This paper presents a wavelet-based method for medical image enhancement. In the proposed method, a transfer function is derived for transferring wavelet coefficients at various multiresolution levels with different weighting values. Applications of the rnethod to digital radiographic images of x-ray chest are shown. Moreover, in order to validate the effectiveness of the proposed method, we compare the results obtained using the wavelet analysis method to that using the conventional fast Fourier transform (FFT) method. The results show that the proposed method is superior to the FFT method in terms of image enhancement.

DOI： 10.1109/ICOSP.2002.1181158

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：The Institute of Electronics, Information and Communication Engineers  

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Other Link： http://hdl.handle.net/10191/6555

Authorship：Lead author   Language：Japanese   Publishing type：Research paper (scientific journal)  

DOI： 10.11318/mii1984.18.135

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Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC  

The purpose of this study is to develop a technique for computer-aided diagnosis (CAD) systems to detect lung nodules in helical X-ray pulmonary computed tomography CT) images. We propose a novel template-matching technique based on a genetic algorithm (GA) template matching (GATM) for detecting nodules existing within the lung area; the GA was used to determine the target position in the observed image efficiently and to select an adequate template image from several reference patterns for quick template matching. In addition, a conventional template matching was employed to detect nodules existing on the lung wall area,lung wall template matching (LWTM), where semicircular models were used as reference patterns; the semicircular models were rotated according to the angle of the target point on the contour of the lung wall. After initial detecting candidates using the two template-matching methods, we extracted a total of 13 feature values and used them to eliminate false-positive findings. Twenty clinical cases involving a total of 557 sectional images were used in this study. 71 nodules out of 98 were correctly detected by our scheme (i,e,, a detection rate of about 72%), with the number of false positives at approximately 1.1/sectional image, Our present results show that our scheme can be regarded as a technique for CAD systems to detect nodules in helical CT pulmonary images.

DOI： 10.1109/42.932744

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DOI： 10.1118/1.1382823

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

This paper presents a fuzzy-reasoning-based computer-aided diagnosis scheme for automated classification of heart disease from ultrasonic images. Unlike the conventional types of membership functions, Gaussian-distributed membership functions (GDMFs) are employed in the present study. The GDMFs are initially generated using various texture-based features computed from gray-level co-occurrence matrices. Subsequently, the shapes of GDMFs are optimized by genetic-algorithm learning process. After optimization, the classifier is used to discriminate two sets of echocardiographic images, namely, normal and abnormal cases, which were diagnosed in advance by a highly trained physician. We experimentally evaluate the performance of the proposed method against various methods been reported in terms of accuracy, sensitivity, and specificity. Experimental results show that the proposed method has potential utility for computer-aided diagnosis of myocardial heart disease.

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：FUDAN UNIV PRESS  

In recent years, considerable and serious efforts have been made toward the development of computer aided diagnosis (CAD) systems in diagnostic radiology. The CAD in radiology is a diagnosis made by a clinician (radiologist) who uses the output from a computerized analysis of medical images as a second opinion. In this paper we describe two CAD systems using artificial neural networks (ANNs). The first system is an application to the segmentation of liver region in computed tomographic images for 3D visualization. The second system is an application to classification of cardiac disease. Results show that the presented systems using the ANNs give considerably satisfactory detection and classification performance.

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Language：Japanese   Publisher：Japanese Society of Radiological Technology  

DOI： 10.6009/jjrt.KJ00003111315

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DOI： 10.11318/mii1984.17.118

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：ELSEVIER SCIENCE BV  

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The purpose of this work is to present some technical approaches of our computer-aided detection (CAD) system for chest radiograms and helical CT scans, and also evaluate that by using three databases. The CAD includes some methods to detect lesions and to eliminate false-positive findings. The detection methods consist of template matching and artificial neural network approaches. A genetic algorithm (GA) was employed in template matching to select a matched image from various reference patterns. Artificial neural networks (ANN) were also applied to eliminate the false-positive candidates. The sensitivity and the number of false-positives were 73% and 11 FP per image on chest radiogram CAD and 77% with 2.6 FP per image on helical CT scan CAD. These preliminary results imply that the GA and ANN-based detection methods may be effective in indicating lesions on chest radiograms and helical CT scans. © 1999 IEEE.

DOI： 10.1109/ICIAP.1999.797688

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：ELSEVIER SCIENCE BV  

The purpose of this work is to present some technical approaches of our computer-aided diagnosis (CAD) system for chest radiograms and helical CT scans, and also evaluate that by using three databases. The CAD includes some methods to detect lesions and to eliminate false-positive findings. The detective methods consist of template matching and artificial neural network approaches. Genetic Algorithm (GA) was employed in template matching to select a matched image from various reference patterns. Artificial Neural Networks (ANN) were also applied to eliminate the false-positive candidates. The sensitivity and the number of false-positives were 73% and 11FPs per image on chest radiogram CAD and 77% with 2.6 FPs per image on helical CT scan CAD. These preliminary results imply that the GA and ANN based detective methods may be effective to indicate lesions on chest radiograms and helical CT scans.

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Language：Japanese   Publisher：The Japanese Society of Medical Imaging Technology  

DOI： 10.11409/mit.16.103

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Other Link： http://search.jamas.or.jp/link/ui/1998177115

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：ELSEVIER SCIENCE BV  

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IEEE COMPUTER SOC  

The purpose of this study is to apply a genetic-algorithm (GA) template-matching method to detect lung nodules in chest helical x-ray CT (computed tomography) images. We combined GA and template matching to search the positions of nodules and to calculate adaptation scales of individuals on GA, respectively. We used four simulated nodules created by Gaussian distribution, whose sizes were different each other, as reference patterns in the GA template matching. The GA selected an adequate reference image from four ones and searched adequate positions to template matching. We used cross-correlation as similarity of tmplate matching and as adaptation scales of individuals on GA. It was possible to detect 23 nodules from 45 ones that did not touch lung walls without consideration of their sizes. It was also possible to detect all nodules that touched lung walls by using conventional template matching along lung walls. The total detection rate was approximately 67%. The number of false positives per one slice was over 10. To improve the detection performance and to decrease the number of false positives, we are now working on considering operators and their parameters of GA.

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Medical Imaging and Information Sciences  

We are developing a computer-aided diagnostic system (CAD) which can detect masses and clustered microcalcifications on digital mammograms. In indicating the computer results to the physicians on an ordinary cathode-ray tube monitor, an automated windowing method has been applied to enhance the shadow of mammary glands. The area near the breast skin lines was difficult to evaluate, because most of pixel values in those areas were ignored by the method. Therefore, the improvement of contrast-correction process is required for the CAD. The purpose of this paper is to describe the dynamic-range compression technique which could make observers easier to recognize the regions in high and/or low density area, and is also to apply the method to the display stage of annotated images in our mammogram CAD.

DOI： 10.11318/mii1984.13.78

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Language：Japanese   Publisher：ニューサイエンス社  

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Language：Japanese   Publisher：日本医用画像工学会  

本研究では、CR画像の総合画質改善を目的として、冗長型離散wavelet展開係数の改良処理により、ノイズの軽減とコントラストの向上を、同時に可能とする処理法を提案する。本提案法では、まず、対象画像にレベル2までの冗長型離散wavelet変換を施し、高周波成分の各レベル・各方向ごとの展開係数間で相関を求めた後、相関値にしきい値処理を施しノイズ除去を行う。次に、高周波成分を指数関数的に強調処理させ、画像のコントラスト改善を図る。本提案手法の優位性を検証するため、よく用いられる他の2手法と比較評価する。その結果、視覚的評価及び物理的評価とも、本提案法が優位であることが示され、提案手法がCR画像の画質改善に有効であることを示唆している。(著者抄録)

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Language：Japanese   Publisher：The Institute of Electronics, Information and Communication Engineers  

Objective evaluation, e.g. using MTF or NPS, of X-ray imaging system may not correctly correspond to subject evaluation, e.g. using ROC. Moreover, it is difficult to measure MTF or NPS from clinical images. Therefore, we introduced MTF fractal dimension to X-ray imaging system. The MTF fractal dimension includes frequency properties of human eyes in addition to quantitative complexity. In this study, we conducted an observer performance study using chest X-ray images with subtle simulated nodules, and also measured MTF fractal dimension from the same images. The measurement results of MTF fractal dimension tended to be similar to the results of observer performance study. Therefore, we consider that MTF fractal dimension may become an index of image quality in medical X-ray imaging system.

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Other Link： http://hdl.handle.net/20.500.12099/53321

Language：Japanese   Publisher：The Institute of Electronics, Information and Communication Engineers  

In this study, we proposed an automated recognition method for blurred radiographs. The method involved edge detection using sobel filter, automatically determining region of interest (ROI), feature calculation, and classification using support vector machine. We applied our method to 14 phantom images (7 normal images, 7 blurred images) and 14 clinical images (12 normal images, 2 blurred images). As a result, the classification accuracies of images with blurs and images without blurs were 100% for both phantom and clinical images.

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Language：Japanese   Publisher：新潟大学教育・学生支援機構  

平成23年度新潟大学組織的教育プログラム(新潟大学GP)医学部保健学科取組「学生と教員が学び鍛えあう保健学教育」は,医療を支える使命感と能力をもち,チーム医療に対応できる人材の育成をめざす2つの教育プログラムの実質化を進めた.保健学ヘの動機づけを図るプログラム「My confident lecture」では,新規科目「保健学総合」を初年次学生向けに開講し,学生参加型授業などの新しいタイプの授業の試みを行った.「保健学総合」を実践的に展開するプログラム「Our project study」では,少人数型の演習科目「保健学総合演習」の平成24年度開講をめざして模擬授業を試みた.それらの活動内容について,取組の課題とともに紹介する.

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Language：Japanese   Publisher：日本医用画像工学会  

近年、ウェーブレット変換を用いた医用画像のノイズ除去の諸手法が提案されている。本研究では、マンモグラムを対象として、離散ウェーブレット変換を用いた従来型のノイズ除去ならびに離散定常ウェーブレット変換を用いた2種類(従来型、改良型)のノイズ除去を行い、これら3手法の性能を検証する。使用するウェーブレット基底関数は、シミュレーション実験により物理特性評価で決定する。評価指標には、相互情報量、平均二乗誤差、信号雑音比の3つを用いる。性能の検証には、臨床画像実験による処理時間計測と視覚評価を行う。視覚評価には、シェッフェの一対比較中屋変法を用いる。結果は、演算時間が最速なのは、離散ウェーブレット変換を用いた従来型のノイズ除去法であったが、画質の面では離散定常ウェーブレット変換を用いた改良型ノイズ除去法が最良であった。(著者抄録)

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Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (scientific journal)   Publisher：The Japanese Society of Medical Imaging Technology  

Identification of loss of the gray-white matter interface (GWMI) is important for the diagnosis of acute stroke in unenhanced CT. However, the identification is difficult due to the intrinsic presence of quantum noise on CT images. As a result, low sensitivity of detection of loss of the GWMI becomes a major issue in unenhanced CT. To cope with this issue, we have previously developed an adaptive partial median filter (APMF). In order to validate the usefulness of the APMF, we have evaluated the performance of the proposed filter using simulated images and clinical images. This report first describes the outline of the APMF and its performance. Next, the practically clinical usefulness of the APMF is presented based on experimental results.

DOI： 10.11409/mit.30.231

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Other Link： http://search.jamas.or.jp/link/ui/2013203999

Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (scientific journal)   Publisher：日本放射線技術学会画像分科会  

DOI： 10.18973/cigjsrt.35.2_66

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Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (scientific journal)   Publisher：日本放射線技術学会画像分科会  

DOI： 10.18973/cigjsrt.35.1_82

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Language：Japanese   Publisher：The Institute of Electronics, Information and Communication Engineers  

A novel application of computer-aided diagnosis (CAD), namely autonomous CAD, was proposed in this study. Autonomous CAD can obtain medical images in front of it by computer vision (CV), and detect abnormalities from the obtained image, and output the detection result to the position space. Some fundamental techniques are required to materialize the autonomous CAD, e.g. detection algorithm of abnormalities in radiographs, and recognition algorithm of moving radiographs. We developed computerized detection schemes for lung nodules in X-ray images. Sixty chest radiographs and twenty CT scans were used to evaluate the detection schemes. These images were displayed on a monitor, and taken by an optical camera as the CV images. The detection schemes were applied to the obtained CV images. Our results showed that there was no difference in detection performances even if the CV image was used as input of the detection scheme. We also developed a scheme to recognize radiographs in CV moving images. The scheme was applied to ten moving images with scenes including radiographs. It was able to nearly correctly recognize moving radiographs. The developed schemes would become fundamental techniques in future autonomous CAD system.

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Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (scientific journal)   Publisher：The Japanese Society of Medical Imaging Technology  

This paper described a z-score mapping method on the basis of a voxel-by-voxel analysis to visualize hypoattenuation regions of hyperacute stroke on unenhanced CT images. The algorithm of this method consisted of 5 major steps, <I>i.e</I>., anatomic standardization, construction of a normal reference database, calculation of z score, elimination of false positive areas, and extraction of hypoattenuation areas. The performance of this method in detection of hypoattenuation with a series of 21 patients with infarction (< 3 hours) showed the AUC =0.834 for distinction between hypoattenuation and normal regions. The result of an observer study with five neuroragiologists, also, demonstrated the average AUC for detection oh hypoattenuation regions significantly improved from 0.883 to 0.925 (<I>P</I>< 0.01). Therefore, the z-score mapping method could effectively extract hypoattenuation regions that showed a high z-score value on the z-score map. The use of this method has the potential to help neuroradiolgists detect hypoattenuation regions of hyperacute stroke on unenhanced CT images.

DOI： 10.11409/mit.29.17

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Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (other)   Publisher：Japanese Society of Radiological Technology  

DOI： 10.6009/jjrt.66.1614

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Other Link： https://jlc.jst.go.jp/DN/JALC/00362227343?from=CiNii

Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (scientific journal)   Publisher：日本放射線技術学会画像分科会  

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Language：Japanese  

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Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (scientific journal)   Publisher：Japanese Society of Radiological Technology (JSRT)  

Abstract is not available. (Article in Japanese)

DOI： 10.6009/jjrt.64.1000

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Other Link： https://jlc.jst.go.jp/DN/JALC/00317643914?from=CiNii

Language：Japanese   Publisher：The Institute of Electronics, Information and Communication Engineers  

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Other Link： http://search.jamas.or.jp/link/ui/2008298848

Language：Japanese   Publisher：公益社団法人日本放射線技術学会  

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Language：Japanese   Publisher：公益社団法人日本放射線技術学会  

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Language：Japanese   Publisher：公益社団法人日本放射線技術学会  

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Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (scientific journal)   Publisher：日本放射線技術学会画像分科会  

DOI： 10.18973/cigjsrt.30.2_68

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Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (scientific journal)   Publisher：日本放射線技術学会画像分科会  

DOI： 10.18973/cigjsrt.30.1_79

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Language：English   Publisher：Springer New York  

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Language：Japanese   Publisher：公益社団法人日本放射線技術学会  

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Language：Japanese   Publisher：公益社団法人日本放射線技術学会  

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Language：Japanese   Publisher：公益社団法人日本放射線技術学会  

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Language：Japanese   Publisher：公益社団法人日本放射線技術学会  

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Language：Japanese   Publisher：公益社団法人日本放射線技術学会  

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Language：English   Publisher：The Institute of Electronics, Information and Communication Engineers  

We have developed a new recognition approach using 2nd order autocorrelation and multi-regression analysis to detect a small (<7mm in diameter) lung nodules in chest 3D CT images. By combining our previous detection method of the template matching based on genetic algorithm, the detection performance was 94% true-positive rate at 2.05 false-positive marks per case using leave-one-out study.

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Language：Japanese   Publisher：Japanese Society for Medical and Biological Engineering  

The purpose of this study is to develop a computerized scheme that allows discrimination between benign and malignant clustered microcalcifications, thus aiding radiologists to better interpret mammograms. The fuzzy-logic based genetic algorithm (GA-Fuzzy) that we propose is applied for the classification of mammographic microcalcifications. As a preprocess, microcalcification regions are extracted from images using mathematical morphology and other means. Then, four feature values including the number, area, circularity and minimum distance of microcalcifications are calculated for classification using GA-Fuzzy. In the GA-Fuzzy process, Gaussian-distributed membership functions are determined from the means and standard deviations of the feature values calculated from training images. Subsequently, the genetic algorithm optimizes the membership functions, and training is completed. Next, the feature values calculated from unknown images are input into GA-Fuzzy system to classify the image. Our scheme was tested utilizing the database of the Mammographic Image Analysis Society (MIAS), which contains 13 benign and 12 malignant microcalcification cases. Of the images, there are ten of each benign and malignant cases respectively used for training. The remaining five cases were used for classification as unknown images. Various combinations of sets are employed to obtain the results. The average accuracy of the GA-Fuzzy technique was approximately 81% (sensitivity, 85%; specificity, 77%). These results show that our scheme can be regarded as a useful technique to classify microcalcification cases.

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Other Link： http://search.jamas.or.jp/link/ui/2004017840

Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (scientific journal)   Publisher：医用画像情報学会  

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Language：English   Publishing type：Research paper, summary (international conference)   Publisher：RADIOLOGICAL SOC NORTH AMERICA  

Web of Science

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Other Link： http://search.jamas.or.jp/link/ui/2003037691

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Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (scientific journal)   Publisher：日本放射線技術学会画像分科会  

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Language：Japanese   Publisher：The Institute of Electronics, Information and Communication Engineers  

We have proposed a technique, by which a template matching of gray-level images can be performed accurately and fastly in a large range of searching regions, and in which a genetic algorithm(GA)is applied to the searching part in image recognition.The images that we have used were only 2D ones.In this paper, therefore, we applied our method to 3D images by considering an application to 3D medeical images.It was shown based on a simulation study that our method is useful in 3D space.In the application of our techique, the nodule detection on chest helical CT images is effective.

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Language：Japanese   Presentation type：Symposium, workshop panel (nominated)  

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Award type：Award from international society, conference, symposium, etc.  Country：United States

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Award type：Award from international society, conference, symposium, etc.  Country：United States

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Award type：Honored in official journal of a scientific society, scientific journal  Country：Japan

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Award type：Honored in official journal of a scientific society, scientific journal  Country：Japan

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Award type：Honored in official journal of a scientific society, scientific journal  Country：Japan

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Award type：Award from international society, conference, symposium, etc.  Country：United States

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