Dr. Chisako Muramatsu Profile

Dr. Chisako Muramatsu

Professor at Shiga Univ

SPIE Involvement:

Conference Program Committee | Author

Publications (47)

Proceedings Article | 3 April 2024 Poster + Paper

Intrinsic subtype classification of breast cancers on mammograms using local selective patches

Chisako Muramatsu, Mikinao Oiwa, Tomonori Kawasaki, Rieko Nishimura, Hiroshi Fujita

Proceedings Volume 12927, 1292723 (2024) https://doi.org/10.1117/12.3008738

KEYWORDS: Breast cancer, Mammography, Cancer, Oncology, Pathology, Image classification, Diagnostics, Cross validation

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Proceedings Article | 7 April 2023 Poster + Paper

Recognition of tooth numbers and conditions on dental panoramic radiographs for assisting dental chart filing

Chisako Muramatsu, Koki Sakai, Yuta Seino, Ryo Takahashi, Tatsuro Hayashi, Wataru Nishiyama, Xiangrong Zhou, Takeshi Hara, Akitoshi Katsumata, Hiroshi Fujita

Proceedings Volume 12465, 1246539 (2023) https://doi.org/10.1117/12.2655306

KEYWORDS: Teeth, Panoramic photography, Radiography, Object detection, Cross validation, Diagnostics

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Proceedings Article | 13 July 2022 Paper

Classification of intrinsic subtypes and histological grade for breast cancers by multimodality images

Chisako Muramatsu, Takumi Iwasaki, Mikinao Oiwa, Tomonori Kawasaki, Hiroshi Fujita

Proceedings Volume 12286, 122860Y (2022) https://doi.org/10.1117/12.2625871

KEYWORDS: Cancer, Mammography, Ultrasonography, Image classification, Breast cancer, Diagnostics

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SPIE Journal Paper | 22 June 2022

Tooth recognition of 32 tooth types by branched single shot multibox detector and integration processing in panoramic radiographs

Takumi Morishita, Chisako Muramatsu, Yuta Seino, Ryo Takahashi, Tatsuro Hayashi, Wataru Nishiyama, Xiangrong Zhou, Takeshi Hara, Akitoshi Katsumata, Hiroshi Fujita

JMI, Vol. 9, Issue 03, 034503, (June 2022) https://doi.org/10.1117/12.10.1117/1.JMI.9.3.034503

KEYWORDS: Teeth, Sensors, Panoramic photography, Radiography, Target detection, Performance modeling, Image segmentation, Neural networks, Medical imaging, Image classification

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Proceedings Article | 1 May 2022 Paper

Detection and classification of 32 tooth types in dental panoramic radiographs using single CNN model and post-processing

Takumi Morishita, Chisako Muramatsu, Yuta Seino, Ryo Takahashi, Tatsuro Hayashi, Wataru Nishiyama, Xiangrong Zhou, Takeshi Hara, Akitoshi Katsumata, Hiroshi Fujita

Proceedings Volume 12177, 121771T (2022) https://doi.org/10.1117/12.2625961

KEYWORDS: Teeth, Radiography, Panoramic photography, Image classification, Target detection, Target recognition, Sensors, Medical imaging, Image processing, Dentistry

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Proceedings Article | 4 April 2022 Poster + Presentation + Paper

Intrinsic subtype classification of breast lesions on mammograms by contrastive learning

Chisako Muramatsu, Mikinao Oiwa, Tomonori Kawasaki, Hiroshi Fujita

Proceedings Volume 12033, 120331S (2022) https://doi.org/10.1117/12.2613173

KEYWORDS: Mammography, Breast, Cancer, Image classification, Breast cancer, Diagnostics

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Proceedings Article | 15 February 2021 Poster + Presentation + Paper

Tooth recognition and classification using multi-task learning and post-processing in dental panoramic radiographs

Takumi Morishita, Chisako Muramatsu, Xiangrong Zhou, Ryo Takahashi, Tatsuro Hayashi, Wataru Nishiyama, Takeshi Hara, Yoshiko Ariji, Eiichiro Ariji, Akitoshi Katsumata, Hiroshi Fujita

Proceedings Volume 11597, 115971X (2021) https://doi.org/10.1117/12.2582046

KEYWORDS: Teeth, Radiography, Panoramic photography, Sensors, Image classification

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Proceedings Article | 22 May 2020 Paper

Mammographic mass identification in dense breasts using multi-scale analysis of structured micro-patterns

Shelda Sajeev, Mariusz Bajger, Gobert Lee, Chisako Muramatsu, Hiroshi Fujita

Proceedings Volume 11513, 1151323 (2020) https://doi.org/10.1117/12.2564272

KEYWORDS: Mammography, Breast, Breast cancer, Digital filtering, Tissues, Binary data, Databases, Cancer, Computer aided diagnosis and therapy, Feature extraction

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Proceedings Article | 22 May 2020 Paper

Breast mass image retrieval based on multimodality similarity estimation

Chisako Muramatsu, Mikinao Oiwa, Tomonori Kawasaki, Hiroshi Fujita

Proceedings Volume 11513, 1151326 (2020) https://doi.org/10.1117/12.2564048

KEYWORDS: Image retrieval, Mammography, Breast, Ultrasonography, Convolutional neural networks, Image analysis, Digital mammography, Breast cancer

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Proceedings Article | 2 March 2020 Paper

Detection of defected nerve regions on retinal fundus images using OCT data for glaucoma screening

Chisako Muramatsu, Ryusuke Watanabe, Akira Sawada, Yuji Hatanaka, Takeshi Hara, Tetsuya Yamamoto, Hiroshi Fujita

Proceedings Volume 11318, 1131819 (2020) https://doi.org/10.1117/12.2549920

KEYWORDS: Optical coherence tomography, Photography, Image segmentation, Defect detection, Image registration, Visualization, Ophthalmology, Blood vessels

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Proceedings Article | 2 March 2020 Paper

Tooth numbering in cone-beam CT using a relation network for automatic filing of dentition charts

Chisako Muramatsu, Shota Kutsuna, Ryo Takahashi, Tatsuro Hayashi, Wataru Nishiyama, Yoshiko Ariji, Xiangrong Zhou, Takeshi Hara, Akitoshi Katsumata, Eiichiro Ariji, Hiroshi Fujita

Proceedings Volume 11318, 113180L (2020) https://doi.org/10.1117/12.2550933

KEYWORDS: Teeth, Computed tomography, Image segmentation, Dentistry, Diagnostics, Forensic science, Databases

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Proceedings Article | 27 March 2019 Paper

Initial study on the classification of amyotrophic diseases using texture analysis and deep learning in whole-body CT images

N. Kamiya, A. Oshima, E. Asano, X. Zhou, M. Yamada, H. Kato, C. Muramatsu, T. Hara, T. Miyoshi, M. Matsuo, H. Fujita

Proceedings Volume 11050, 110500X (2019) https://doi.org/10.1117/12.2518199

KEYWORDS: Computed tomography, Statistical analysis, Image classification, Inspection, Radiology, Visualization, Computer aided diagnosis and therapy, Analytical research, Information science, Information technology

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Proceedings Article | 27 March 2019 Paper

Arteriovenous classification method using convolutional neural network for early detection of retinal vascular lesion

Hibiki Ikawa, Yuji Hatanaka, Wataru Sunayama, Kazunori Ogohara, Chisako Muramatsu, Hiroshi Fujita

Proceedings Volume 11050, 110501M (2019) https://doi.org/10.1117/12.2521528

KEYWORDS: Blood vessels, Arteries, Veins, Image segmentation, Convolutional neural networks, Image classification, Image resolution, Electronics engineering, Systems engineering, Performance modeling

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Proceedings Article | 15 March 2019 Paper

Image retrieval of breast masses on ultrasound images

Chisako Muramatsu, Shunichi Higuchi, Takako Morita, Mikinao Oiwa, Tomonori Kawasaki, Hiroshi Fujita

Proceedings Volume 10955, 1095517 (2019) https://doi.org/10.1117/12.2513663

KEYWORDS: Image retrieval, Ultrasonography, Breast, Data modeling, 3D modeling, Gold, Diagnostics, Mammography, Image analysis, Network architectures

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Proceedings Article | 6 July 2018 Paper

Retrieval of reference images of breast masses on mammograms by similarity space modeling

Chisako Muramatsu, Shunichi Higuchi, Takako Morita, Mikinao Oiwa, Tomonori Kawasaki, Hiroshi Fujita

Proceedings Volume 10718, 1071809 (2018) https://doi.org/10.1117/12.2318717

KEYWORDS: Image retrieval, Mammography, Breast, Digital mammography, Visualization, Diagnostics, Convolutional neural networks, Breast cancer

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Proceedings Article | 27 February 2018 Paper

Chisako Muramatsu, Shunichi Higuchi, Takako Morita, Mikinao Oiwa, Hiroshi Fujita

Proceedings Volume 10575, 105752U (2018) https://doi.org/10.1117/12.2293979

KEYWORDS: Image retrieval, Mammography, Feature extraction, Convolutional neural networks, Digital mammography, Image analysis, Breast, Diagnostics, Breast cancer, Neural networks

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Proceedings Article | 3 March 2017 Paper

Automated detection of masses on whole breast volume ultrasound scanner: false positive reduction using deep convolutional neural network

Yuya Hiramatsu, Chisako Muramatsu, Hironobu Kobayashi, Takeshi Hara, Hiroshi Fujita

Proceedings Volume 10134, 101342S (2017) https://doi.org/10.1117/12.2254581

KEYWORDS: Convolutional neural networks, Breast, Ultrasonography, Neural networks, Mammography, Breast cancer, Computer-aided diagnosis, Machine learning, Statistical modeling, Image filtering, Receivers

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Proceedings Article | 3 March 2017 Paper

Automated analysis of whole skeletal muscle for muscular atrophy detection of ALS in whole-body CT images: preliminary study

Naoki Kamiya, Kosuke Ieda, Xiangrong Zhou, Megumi Yamada, Hiroki Kato, Chisako Muramatsu, Takeshi Hara, Toshiharu Miyoshi, Takashi Inuzuka, Masayuki Matsuo, Hiroshi Fujita

Proceedings Volume 10134, 1013442 (2017) https://doi.org/10.1117/12.2251584

KEYWORDS: Computed tomography, Computer aided diagnosis and therapy, Solid modeling, Diagnostics, Inspection, Image segmentation, Visualization, Computer aided design, Abdomen, Lung, 3D modeling, Medicine, Radiology

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Amyotrophic lateral sclerosis (ALS) causes functional disorders such as difficulty in breathing and swallowing through the atrophy of voluntary muscles. ALS in its early stages is difficult to diagnose because of the difficulty in differentiating it from other muscular diseases. In addition, image inspection methods for aggressive diagnosis for ALS have not yet been established. The purpose of this study is to develop an automatic analysis system of the whole skeletal muscle to support the early differential diagnosis of ALS using whole-body CT images. In this study, the muscular atrophy parts including ALS patients are automatically identified by recognizing and segmenting whole skeletal muscle in the preliminary steps. First, the skeleton is identified by its gray value information. Second, the initial area of the body cavity is recognized by the deformation of the thoracic cavity based on the anatomical segmented skeleton. Third, the abdominal cavity boundary is recognized using ABM for precisely recognizing the body cavity. The body cavity is precisely recognized by non-rigid registration method based on the reference points of the abdominal cavity boundary. Fourth, the whole skeletal muscle is recognized by excluding the skeleton, the body cavity, and the subcutaneous fat. Additionally, the areas of muscular atrophy including ALS patients are automatically identified by comparison of the muscle mass. The experiments were carried out for ten cases with abnormality in the skeletal muscle. Global recognition and segmentation of the whole skeletal muscle were well realized in eight cases. Moreover, the areas of muscular atrophy including ALS patients were well identified in the lower limbs. As a result, this study indicated the basic technology to detect the muscle atrophy including ALS. In the future, it will be necessary to consider methods to differentiate other kinds of muscular atrophy as well as the clinical application of this detection method for early ALS detection and examine a large number of cases with stage and disease type.

Proceedings Article | 3 March 2017 Paper

Tooth labeling in cone-beam CT using deep convolutional neural network for forensic identification

Yuma Miki, Chisako Muramatsu, Tatsuro Hayashi, Xiangrong Zhou, Takeshi Hara, Akitoshi Katsumata, Hiroshi Fujita

Proceedings Volume 10134, 101343E (2017) https://doi.org/10.1117/12.2254332

KEYWORDS: Convolutional neural networks, Teeth, Computed tomography, Neural networks, Forensic science, Image classification, Image analysis, Network architectures, Convolution, Imaging systems, Machine learning, X-ray computed tomography, Image segmentation, X-ray imaging, X-rays, Facial recognition systems

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Proceedings Article | 3 March 2017 Paper

Evaluation of age-related changes with cross-sectional CT imaging of teeth

Tatsumasa Fukui, Kanade Kita, Hiromasa Kamemoto, Wataru Nishiyama, Hiroyasu Yoshida, Yukihiro Iida, Akitoshi Katsumata, Chisako Muramatsu, Hiroshi Fujita

Proceedings Volume 10134, 101343C (2017) https://doi.org/10.1117/12.2254012

KEYWORDS: Teeth, Forensic dentistry, Algorithm development, Dentistry, Computed tomography, 3D image processing, Image segmentation, Imaging systems, Radiology, Dental caries

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Proceedings Article | 3 March 2017 Paper

Automated detection of nerve fiber layer defects on retinal fundus images using fully convolutional network for early diagnosis of glaucoma

Ryusuke Watanabe, Chisako Muramatsu, Kyoko Ishida, Akira Sawada, Yuji Hatanaka, Tetsuya Yamamoto, Hiroshi Fujita

Proceedings Volume 10134, 1013438 (2017) https://doi.org/10.1117/12.2254574

KEYWORDS: Convolutional neural networks, Neural networks, Defect detection, Image filtering, Machine learning, Eye, Retina, Visualization, Medicine, Ophthalmology, Receivers, Photography, Gold

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Proceedings Article | 1 April 2016 Paper

Development of estimation system of knee extension strength using image features in ultrasound images of rectus femoris

Hiroki Murakami, Tsuneo Watanabe, Daisuke Fukuoka, Nobuo Terabayashi, Takeshi Hara, Chisako Muramatsu, Hiroshi Fujita

Proceedings Volume 9790, 979012 (2016) https://doi.org/10.1117/12.2214843

KEYWORDS: Ultrasonography, Data modeling, Ultrasonics, Medical imaging, Fourier transforms, Image compression, Edge detection, Error analysis

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Proceedings Article | 24 March 2016 Paper

Automated blood vessel extraction using local features on retinal images

Yuji Hatanaka, Kazuki Samo, Mikiya Tajima, Kazunori Ogohara, Chisako Muramatsu, Susumu Okumura, Hiroshi Fujita

Proceedings Volume 9785, 97852F (2016) https://doi.org/10.1117/12.2216572

KEYWORDS: Blood vessels, Feature extraction, Computer aided design, Image segmentation, Artificial neural networks, Databases, Receivers, Eye, Retina, Image filtering, Optical filters, Blood, Systems engineering

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Proceedings Article | 24 March 2016 Paper

Automated detection of retinal nerve fiber layer defects on fundus images: false positive reduction based on vessel likelihood

Chisako Muramatsu, Kyoko Ishida, Akira Sawada, Yuji Hatanaka, Tetsuya Yamamoto, Hiroshi Fujita

Proceedings Volume 9785, 97852L (2016) https://doi.org/10.1117/12.2216662

KEYWORDS: Nerve, Blood vessels, Eye, Retina, Databases, Image filtering, Digital filtering, Medicine, Ophthalmology, Photography, Visualization

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Proceedings Article | 24 March 2016 Paper

Automated recognition of the iliac muscle and modeling of muscle fiber direction in torso CT images

N. Kamiya, X. Zhou, K. Azuma, C. Muramatsu, T. Hara, H. Fujita

Proceedings Volume 9785, 97853K (2016) https://doi.org/10.1117/12.2214613

KEYWORDS: Computed tomography, Databases, Data modeling, Visualization, Image segmentation, CAD systems, Laser induced plasma spectroscopy, Feature extraction, Intestine, Medicine, Solid modeling, Quantitative analysis

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Proceedings Article | 20 March 2015 Paper

Automated classification of mandibular cortical bone on dental panoramic radiographs for early detection of osteoporosis

Kazuki Horiba, Chisako Muramatsu, Tatsuro Hayashi, Tatsumasa Fukui, Takeshi Hara, Akitoshi Katsumata, Hiroshi Fujita

Proceedings Volume 9414, 94142J (2015) https://doi.org/10.1117/12.2081512

KEYWORDS: Bone, Computer aided diagnosis and therapy, Panoramic photography, Radiography, FDA class I medical device development, Computing systems, Dentistry, Minerals, FDA class II medical device development, Neodymium

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Proceedings Article | 20 March 2015 Paper

Semi-automated measurements of heart-to-mediastinum ratio on 123I-MIBG myocardial scintigrams by using image fusion method with chest X-ray images

Ryosuke Kawai, Takeshi Hara, Tetsuro Katafuchi, Tadahiko Ishihara , Xiangrong Zhou, Chisako Muramatsu, Yoshiteru Abe, Hiroshi Fujita

Proceedings Volume 9414, 941433 (2015) https://doi.org/10.1117/12.2081630

KEYWORDS: Chest, Image fusion, Heart, Image segmentation, Chest imaging, Lung, Neodymium, Medicine, Diagnostics, Dementia

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MIBG (iodine-123-meta-iodobenzylguanidine) is a radioactive medicine that is used to help diagnose not only myocardial diseases but also Parkinson’s diseases (PD) and dementia with Lewy Bodies (DLB). The difficulty of the segmentation around the myocardium often reduces the consistency of measurement results. One of the most common measurement methods is the ratio of the uptake values of the heart to mediastinum (H/M). This ratio will be a stable independent of the operators when the uptake value in the myocardium region is clearly higher than that in background, however, it will be unreliable indices when the myocardium region is unclear because of the low uptake values. This study aims to develop a new measurement method by using the image fusion of three modalities of MIBG scintigrams, 201-Tl scintigrams, and chest radiograms, to increase the reliability of the H/M measurement results. Our automated method consists of the following steps: (1) construct left ventricular (LV) map from 201-Tl myocardium image database, (2) determine heart region in chest radiograms, (3) determine mediastinum region in chest radiograms, (4) perform image fusion of chest radiograms and MIBG scintigrams, and 5) perform H/M measurements on MIBG scintigrams by using the locations of heart and mediastinum determined on the chest radiograms. We collected 165 cases with 201-Tl scintigrams and chest radiograms to construct the LV map. Another 65 cases with MIBG scintigrams and chest radiograms were also collected for the measurements. Four radiological technologists (RTs) manually measured the H/M in the MIBG images. We compared the four RTs’ results with our computer outputs by using Pearson’s correlation, the Bland-Altman method, and the equivalency test method. As a result, the correlations of the H/M between four the RTs and the computer were 0.85 to 0.88. We confirmed systematic errors between the four RTs and the computer as well as among the four RTs. The variation range of the H/M among the four RTs was obtained as 0.22 based on the equivalency test method. The computer outputs were existed within this range. We concluded that our image fusion method could measure equivalent values between the system and the RTs.

Proceedings Article | 18 March 2014 Paper

An automatic early stage alveolar-bone-resorption evaluation method on digital dental panoramic radiographs

Min Zhang, Akitoshi Katsumata, Chisako Muramatsu, Takeshi Hara, Hiroki Suzuki, Hiroshi Fujita

Proceedings Volume 9035, 90353G (2014) https://doi.org/10.1117/12.2044348

KEYWORDS: Image filtering, Panoramic photography, Radiography, Bone, Teeth, Feature extraction, Visualization, X-rays, Radiology, X-ray imaging

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Proceedings Article | 18 March 2014 Paper

Toward early diagnosis of arteriosclerotic diseases: collaborative detection of carotid artery calcifications by computer and dentists on dental panoramic radiographs

Chisako Muramatsu, Ryo Takahashi, Takeshi Hara, Tatsuro Hayashi, Akitoshi Katsumata, Xiangrong Zhou, Hiroshi Fujita

Proceedings Volume 9035, 903521 (2014) https://doi.org/10.1117/12.2043407

KEYWORDS: Panoramic photography, Computer aided diagnosis and therapy, Radiography, Arteries, Teleradiology, Diagnostics, Feature selection, Imaging systems, Clinical trials, Image processing

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Proceedings Article | 18 March 2014 Paper

Preliminary study on differentiation between glaucomatous and non-glaucomatous eyes on stereo fundus images using cup gradient models

Chisako Muramatsu, Yuji Hatanaka, Kyoko Ishida, Akira Sawada, Tetsuya Yamamoto, Hiroshi Fujita

Proceedings Volume 9035, 903533 (2014) https://doi.org/10.1117/12.2043409

KEYWORDS: Eye models, Image segmentation, Eye, Model-based design, Systems modeling, Photography, Cameras, Databases, Medicine, Ophthalmology

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Proceedings Article | 18 March 2013 Paper

Pulmonary emphysema classification based on an improved texton learning model by sparse representation

Min Zhang, Xiangrong Zhou, Satoshi Goshima, Huayue Chen, Chisako Muramatsu, Takeshi Hara, Ryujiro Yokoyama, Masayuki Kanematsu, Hiroshi Fujita

Proceedings Volume 8670, 86700F (2013) https://doi.org/10.1117/12.2007934

KEYWORDS: Emphysema, Associative arrays, Image classification, Computed tomography, Lung, Chronic obstructive pulmonary disease, Chemical species, 3D image processing, Tissues, Signal attenuation

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Proceedings Article | 28 February 2013 Paper

Preliminary investigation on CAD system update: effect of selection of new cases on classifier performance

Chisako Muramatsu, Kohei Nishimura, Takeshi Hara, Hiroshi Fujita

Proceedings Volume 8670, 86701T (2013) https://doi.org/10.1117/12.2007355

KEYWORDS: Data modeling, CAD systems, Databases, Computer aided diagnosis and therapy, Tumor growth modeling, Computing systems, Mammography, Statistical modeling, Performance modeling, Receivers

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Proceedings Article | 28 February 2013 Paper

Psychophysical similarity measure based on multi-dimensional scaling for retrieval of similar images of breast masses on mammograms

Kohei Nishimura, Chisako Muramatsu, Mikinao Oiwa, Misaki Shiraiwa, Tokiko Endo, Kunio Doi, Hiroshi Fujita

Proceedings Volume 8670, 86701R (2013) https://doi.org/10.1117/12.2001037

KEYWORDS: Image retrieval, Mammography, Breast, Cancer, Computer aided diagnosis and therapy, CAD systems, Radiology, Artificial neural networks, Oncology, Computing systems

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Proceedings Article | 28 February 2013 Paper

Automated detection of abnormalities in paranasal sinus on dental panoramic radiographs by using contralateral subtraction technique based on mandible contour

Shintaro Mori, Takeshi Hara, Motoki Tagami, Chicako Muramatsu, Takashi Kaneda, Akitoshi Katsumata, Hiroshi Fujita

Proceedings Volume 8670, 86702R (2013) https://doi.org/10.1117/12.2007820

KEYWORDS: Inflammation, Panoramic photography, Radiography, Image registration, Computer aided design, CAD systems, Teeth, Receivers, Feature extraction

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Proceedings Article | 28 February 2013 Paper

Temporal subtraction system on torso FDG-PET scans based on statistical image analysis

Yusuke Shimizu, Takeshi Hara, Daisuke Fukuoka, Xiangrong Zhou, Chisako Muramatsu, Satoshi Ito, Kenta Hakozaki, Shin-ichiro Kumita, Kei-ichi Ishihara, Tetsuro Katafuchi, Hiroshi Fujita

Proceedings Volume 8670, 86703F (2013) https://doi.org/10.1117/12.2007886

KEYWORDS: Cancer, Computer aided diagnosis and therapy, Statistical image analysis, Diagnostics, Neodymium, Computing systems, Imaging systems, Medical imaging, CAD systems

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Proceedings Article | 23 February 2012 Paper

A new screening pathway for identifying asymptomatic patients using dental panoramic radiographs

Tatsuro Hayashi, Takuya Matsumoto, Tsuyoshi Sawagashira, Motoki Tagami, Akitoshi Katsumata, Yoshinori Hayashi, Chisako Muramatsu, Xiangrong Zhou, Yukihiro Iida, Masato Matsuoka, Kiyoji Katagi, Hiroshi Fujita

Proceedings Volume 8315, 83152K (2012) https://doi.org/10.1117/12.911791

KEYWORDS: Panoramic photography, CAD systems, Computer aided diagnosis and therapy, Radiography, Picture Archiving and Communication System, Arteries, Clinical trials, Computer aided design, Image processing, Medical imaging

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Proceedings Article | 23 February 2012 Paper

Automated scheme for measuring mandibular cortical thickness on dental panoramic radiographs for osteoporosis screening

T. Matsumoto, T. Hayashi, T. Hara, A. Katsumata, C. Muramatsu, X. Zhou, Y. Iida, M. Matsuoka, Ki. Katagi, H. Fujita

Proceedings Volume 8315, 83152L (2012) https://doi.org/10.1117/12.912309

KEYWORDS: Panoramic photography, Radiography, Bone, CAD systems, Computer aided diagnosis and therapy, Clinical trials, Sensors, Information technology, Radiology, Minerals

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Proceedings Article | 23 February 2012 Paper

An application to pulmonary emphysema classification based on model of texton learning by sparse representation

Min Zhang, Xiangrong Zhou, Satoshi Goshima, Huayue Chen, Chisako Muramatsu, Takeshi Hara, Ryojiro Yokoyama, Masayuki Kanematsu, Hiroshi Fujita

Proceedings Volume 8315, 831534 (2012) https://doi.org/10.1117/12.912454

KEYWORDS: Emphysema, Image classification, Associative arrays, Tissues, Lung, Computed tomography, Chronic obstructive pulmonary disease, Computer aided diagnosis and therapy, Medical imaging, Distance measurement

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SPIE Journal Paper | 1 September 2011 Open Access

Automated determination of cup-to-disc ratio for classification of glaucomatous and normal eyes on stereo retinal fundus images

Chisako Muramatsu, Hiroshi Fujita, Toshiaki Nakagawa, Akira Sawada, Tetsuya Yamamoto, Yuji Hatanaka

JBO, Vol. 16, Issue 09, 096009, (September 2011) https://doi.org/10.1117/12.10.1117/1.3622755

KEYWORDS: Image segmentation, Image classification, Diagnostics, Eye, Image processing, Digital filtering, Databases, Visualization, Photography, Image filtering

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Proceedings Article | 9 March 2011 Paper

Automatic arteriovenous crossing phenomenon detection on retinal fundus images

Yuji Hatanaka, Chisako Muramatsu, Takeshi Hara, Hiroshi Fujita

Proceedings Volume 7963, 79633V (2011) https://doi.org/10.1117/12.877232

KEYWORDS: Veins, Arteries, Blood vessels, Image filtering, Computer aided diagnosis and therapy, Diagnostics, Capillaries, Detector development, Image segmentation, Retina

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Proceedings Article | 9 March 2010 Paper

Automated detection and classification of major retinal vessels for determination of diameter ratio of arteries and veins

Chisako Muramatsu, Yuji Hatanaka, Tatsuhiko Iwase, Takeshi Hara, Hiroshi Fujita

Proceedings Volume 7624, 76240J (2010) https://doi.org/10.1117/12.843898

KEYWORDS: Arteries, Veins, Image segmentation, Blood vessels, Gold, Databases, Image classification, Image filtering, Digital imaging, Blood pressure

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Proceedings Article | 9 March 2010 Paper

Vertical cup-to-disc ratio measurement for diagnosis of glaucoma on fundus images

Yuji Hatanaka, Atsushi Noudo, Chisako Muramatsu, Akira Sawada, Takeshi Hara, Tetsuya Yamamoto, Hiroshi Fujita

Proceedings Volume 7624, 76243C (2010) https://doi.org/10.1117/12.843775

KEYWORDS: Blood vessels, Computer aided diagnosis and therapy, Cameras, Medicine, Edge detection, Ear, Diagnostics, Optical filters, Image filtering, Channel projecting optics

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SPIE Journal Paper | 1 January 2010 Open Access

Detection of retinal nerve fiber layer defects on retinal fundus images for early diagnosis of glaucoma

Chisako Muramatsu, Yoshinori Hayashi, Akira Sawada, Yuji Hatanaka, Takeshi Hara, Tetsuya Yamamoto, Hiroshi Fujita

JBO, Vol. 15, Issue 01, 016021, (January 2010) https://doi.org/10.1117/12.10.1117/1.3322388

KEYWORDS: Image filtering, Blood vessels, Optical discs, Nerve, Computing systems, Databases, Medicine, Photography, Gaussian filters, Visualization

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Proceedings Article | 5 March 2009 Open Access

Automated microaneurysm detection method based on double ring filter in retinal fundus images

Atsushi Mizutani, Chisako Muramatsu, Yuji Hatanaka, Shinsuke Suemori, Takeshi Hara, Hiroshi Fujita

Proceedings Volume 7260, 72601N (2009) https://doi.org/10.1117/12.813468

KEYWORDS: Blood vessels, Gold, Databases, Image filtering, CAD systems, Computer aided diagnosis and therapy, Image classification, Artificial neural networks, Angiography, Image processing

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Proceedings Article | 3 March 2009 Open Access

Determination of cup-to-disc ratio of optical nerve head for diagnosis of glaucoma on stereo retinal fundus image pairs

Chisako Muramatsu, Toshiaki Nakagawa, Akira Sawada, Yuji Hatanaka, Takeshi Hara, Tetsuya Yamamoto, Hiroshi Fujita

Proceedings Volume 7260, 72603L (2009) https://doi.org/10.1117/12.811461

KEYWORDS: Image enhancement, Image processing, Head, Nerve, 3D image reconstruction, Cameras, Stereoscopic cameras, Receivers, Eye, Computer aided diagnosis and therapy

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Proceedings Article | 3 March 2009 Open Access

Presentation of similar images for diagnosis of breast masses on mammograms: analysis of the effect on residents

Chisako Muramatsu, Robert Schmidt, Junji Shiraishi, Qiang Li, Hiroshi Fujita, Kunio Doi

Proceedings Volume 7260, 72600R (2009) https://doi.org/10.1117/12.811447

KEYWORDS: Breast, Mammography, Databases, Radiology, Cancer, Diagnostics, Visualization, Computer aided diagnosis and therapy, Receivers, Breast cancer

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Proceedings Article | 30 March 2007 Paper

Determination of subjective and objective similarity for pairs of masses on mammograms for selection of similar images

Chisako Muramatsu, Qiang Li, Robert Schmidt, Junji Shiraishi, Kenji Suzuki, Gillian Newstead, Kunio Doi

Proceedings Volume 6514, 65141I (2007) https://doi.org/10.1117/12.713785

KEYWORDS: Mammography, Breast cancer, Breast, Pathology, Artificial neural networks, Computer aided diagnosis and therapy, Databases, Lithium, Cancer, Lung

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Showing 5 of 47 publications

Conference Committee Involvement (4)

Computer-Aided Diagnosis

17 February 2025 | San Diego, California, United States

Computer-Aided Diagnosis

19 February 2024 | San Diego, California, United States

Computer-Aided Diagnosis

20 February 2023 | San Diego, California, United States

Computer-Aided Diagnosis

21 February 2022 | San Diego, California, United States

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