Prof. Mikio Matsuhiro Profile

Prof. Mikio Matsuhiro

at Tokushima Univ

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Author

Publications (25)

Proceedings Article | 10 April 2023 Paper

Micro-nodule analysis by severity of pneumoconiosis using 3D CT images.

Y. Hashimoto, M. Matsuhiro, H. Suzuki, Y. Kawata, Y. Ohtuka, T. Kishimoto, K. Ashizawa, N. Niki

Proceedings Volume 12469, 124690X (2023) https://doi.org/10.1117/12.2653766

KEYWORDS: Lung, 3D image processing, X-ray computed tomography, Pulmonary disorders, Computed tomography, X-rays, Radiography, Matrices, Image analysis, Databases

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Proceedings Article | 4 April 2022 Presentation + Paper

Lobe-specific micro-nodule analysis of pneumoconiosis progression using 3D CT images

Y. Hashimoto, M. Matsuhiro, H. Suzuki, Y. Kawata, Y. Ohtsuka, T. Kishimoto, K. Ashizawa, N. Niki

Proceedings Volume 12037, 120370H (2022) https://doi.org/10.1117/12.2612812

KEYWORDS: Lung, 3D image processing, X-ray computed tomography, Computed tomography, X-rays, Radiography, Image analysis, X-ray imaging, Pulmonary disorders, Injuries

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Proceedings Article | 4 April 2022 Poster + Paper

Segmentation of aorta and main pulmonary artery of non-contrast CT images using U-Net for chronic thromboembolic pulmonary hypertension: evaluation of robustness to contacts with blood vessels

Hidenobu Suzuki, Mikio Matsuhiro, Yoshiki Kawata, Toshihiko Sugiura, Nobuhiro Tanabe, Masahiko Kusumoto, Masahiro Kaneko, Noboru Niki

Proceedings Volume 12033, 1203325 (2022) https://doi.org/10.1117/12.2612705

KEYWORDS: Aorta, Image segmentation, Computed tomography, Arteries, Pulmonary hypertension, Blood vessels

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Proceedings Article | 4 April 2022 Presentation + Paper

Visualization and unsupervised clustering of emphysema progression using t-SNE analysis of longitudinal CT images and SNPs

Hidenobu Suzuki, Mikio Matsuhiro, Yoshiki Kawata, Issei Imoto, Yasutaka Nakano, Masahiko Kusumoto, Masahiro Kaneko, Noboru Niki

Proceedings Volume 12033, 120331H (2022) https://doi.org/10.1117/12.2609296

KEYWORDS: Emphysema, Lung, Visualization, Computed tomography, Visual analytics, Image segmentation, Chronic obstructive pulmonary disease, Stochastic processes, Image analysis, Signal attenuation

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Proceedings Article | 4 April 2022 Presentation + Paper

Renal tumor analysis using multi-phase abdominal CT images

Kento Nishihira, Hidenobu Suzuki, Mikio Matsuhiro, Yoshiki Kawata, Yuuki Kobari, Atsushi Ikeda, Noboru Niki

Proceedings Volume 12033, 120330Q (2022) https://doi.org/10.1117/12.2611354

KEYWORDS: Kidney, Tumors, Computed tomography, Rigid registration, Image segmentation, 3D image processing, Image registration, Cancer, Image analysis, Feature extraction

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Proceedings Article | 15 February 2021 Poster + Paper

Fully automatic bone segmentation through contrast enhanced torso CT dataset

Ahmed Maklad, Hassan Hashem, Mikio Matsuhiro, Hidenobu Suzuki, Noboru Niki

Proceedings Volume 11597, 115972G (2021) https://doi.org/10.1117/12.2582161

KEYWORDS: Bone, Image segmentation, Spine, Solids, Image registration, Computed tomography

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Proceedings Article | 16 March 2020 Paper

Association analysis of SNPs with CT image-based phenotype of emphysema progression in heavy smokers

Hidenobu Suzuki, Mikio Matsuhiro, Yoshiki Kawata, Noboru Niki, Issei Imoto, Yasutaka Nakano, Masahiko Kusumoto, Masahiro Kaneko

Proceedings Volume 11314, 113142D (2020) https://doi.org/10.1117/12.2549431

KEYWORDS: Computed tomography, Emphysema, Lung, Chronic obstructive pulmonary disease, Image segmentation, Genetics, Signal attenuation, Cancer, Lung cancer, Polymers

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Proceedings Article | 27 March 2019 Paper

Deep radiomic precision CT imaging for prognostic biomarkers for interstitial lung diseases

Tomoki Uemura, Mikio Matsuhiro, Chinatsu Watari, Janne Näppi, Radin Nasirudin, Toru Hironaka, Yoshiki Kawata, Noboru Niki, Hiroyuki Yoshida

Proceedings Volume 10954, 109541E (2019) https://doi.org/10.1117/12.2512058

KEYWORDS: Lung, Computed tomography, Image analysis, Performance modeling, Convolutional neural networks, Pulmonary function tests, Statistical analysis, Physiology, Gallium nitride, Feature extraction

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Proceedings Article | 13 March 2019 Paper

Metastatic lymph node analysis of colorectal cancer using quadruple-phase CT images

Keisuke Bando, Ren Nishimoto, Mikio Matsuhiro, Hidenobu Suzuki, Yoshiki Kawata, Noboru Niki, Gen Iinuma

Proceedings Volume 10950, 109503U (2019) https://doi.org/10.1117/12.2512738

KEYWORDS: Lymphatic system, Computed tomography, Veins, Colorectal cancer, Cancer, Arteries, Data modeling, Tumors, Quantitative analysis, Image analysis

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Proceedings Article | 6 March 2018 Paper

Radiomic texture-curvature (RTC) features for precision medicine of patients with rheumatoid arthritis-associated interstitial lung disease

Chinatsu Watari, Mikio Matsuhiro, Janne Näppi, Radin Nasirudin, Toru Hironaka, Yoshiki Kawata, Noboru Niki, Hiroyuki Yoshida

Proceedings Volume 10579, 105791N (2018) https://doi.org/10.1117/12.2294043

KEYWORDS: Lung, Computed tomography, Feature extraction, Chest, Pulmonary function tests

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Proceedings Article | 28 February 2018 Paper

Deep radiomic prediction with clinical predictors of the survival in patients with rheumatoid arthritis-associated interstitial lung diseases

Radin Nasirudina, Janne Näppi, Chinatsu Watari, Mikio Matsuhiro, Toru Hironaka, Shoji Kido, Hiroyuki Yoshida

Proceedings Volume 10575, 105753R (2018) https://doi.org/10.1117/12.2293374

KEYWORDS: Lung, Computed tomography, Feature extraction, Performance modeling, Pulmonary function tests, Convolutional neural networks

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We developed and evaluated the effect of our deep-learning-derived radiomic features, called deep radiomic features (DRFs), together with their combination with clinical predictors, on the prediction of the overall survival of patients with rheumatoid arthritis-associated interstitial lung disease (RA-ILD). We retrospectively identified 70 RA-ILD patients with thin-section lung CT and pulmonary function tests. An experienced observer delineated regions of interest (ROIs) from the lung regions on the CT images, and labeled them into one of four ILD patterns (ground-class opacity, reticulation, consolidation, and honeycombing) or a normal pattern. Small image patches centered at individual pixels on these ROIs were extracted and labeled with the class of the ROI to which the patch belonged. A deep convolutional neural network (DCNN), which consists of a series of convolutional layers for feature extraction and a series of fully connected layers, was trained and validated with 5-fold cross-validation for classifying the image patches into one of the above five patterns. A DRF vector for each patch was identified as the output of the last convolutional layer of the DCNN. Statistical moments of each element of the DRF vectors were computed to derive a DRF vector that characterizes the patient. The DRF vector was subjected to a Cox proportional hazards model with elastic-net penalty for predicting the survival of the patient. Evaluation was performed by use of bootstrapping with 2,000 replications, where concordance index (C-index) was used as a comparative performance metric. Preliminary results on clinical predictors, DRFs, and their combinations thereof showed (a) Gender and Age: C-index 64.8% [95% confidence interval (CI): 51.7, 77.9]; (b) gender, age, and physiology (GAP index): C-index: 78.5% [CI: 70.50 86.51], P < 0.0001 in comparison with (a); (c) DRFs: C-index 85.5% [CI: 73.4, 99.6], P < 0.0001 in comparison with (b); and (d) DRF and GAP: C-index 91.0% [CI: 84.6, 97.2], P < 0.0001 in comparison with (c). Kaplan-Meier survival curves of patients stratified to low- and high-risk groups based on the DRFs showed a statistically significant (P < 0.0001) difference. The DRFs outperform the clinical predictors in predicting patient survival, and a combination of the DRFs and GAP index outperforms either one of these predictors. Our results indicate that the DRFs and their combination with clinical predictors provide an accurate prognostic biomarker for patients with RA-ILD.

Proceedings Article | 27 February 2018 Paper

Automatic blood vessel based-liver segmentation using the portal phase abdominal CT

Ahmed Maklad, Mikio Matsuhiro, Hidenobu Suzuki, Yoshiki Kawata, Noboru Niki, Mitsuo Shimada, Gen Iinuma

Proceedings Volume 10575, 1057527 (2018) https://doi.org/10.1117/12.2293581

KEYWORDS: Liver, Image segmentation, Blood vessels, Bone, Aorta, Veins, Heart, Kidney, Spine

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Proceedings Article | 27 February 2018 Paper

Quantitative assessment for pneumoconiosis severity diagnosis using 3D CT images

Koki Hino, Mikio Matsuhiro, Hidenobu Suzuki, Yoshiki Kawata, Noboru Niki, Katsuya Kato, Takumi Kishimoto, Kazuto Ashizawa

Proceedings Volume 10575, 105753J (2018) https://doi.org/10.1117/12.2293436

KEYWORDS: Lung, Computed tomography, Computer aided diagnosis and therapy, Diagnostics

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Proceedings Article | 27 February 2018 Paper

Computer aided detection system for Osteoporosis using low dose thoracic 3D CT images

Daisuke Tsuji, Mikio Matsuhiro, Hidenobu Suzuki, Yoshiki Kawata, Noboru Niki, Yasutaka Nakano, Masafumi Harada, Masahiko Kusumoto, Takaaki Tsuchida, Kenji Eguchi, Masahiro Kaneko

Proceedings Volume 10575, 105753D (2018) https://doi.org/10.1117/12.2293483

KEYWORDS: Bone, Computed tomography, 3D image processing, Spine, Algorithm development, Computer aided diagnosis and therapy, Computing systems, Image analysis, Chest

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Proceedings Article | 3 March 2017 Paper

A hybrid 3D region growing and 4D curvature analysis-based automatic abdominal blood vessel segmentation through contrast enhanced CT

Ahmed Maklad, Mikio Matsuhiro, Hidenobu Suzuki, Yoshiki Kawata, Noboru Niki, Mitsuo Shimada, Gen Iinuma

Proceedings Volume 10134, 101344C (2017) https://doi.org/10.1117/12.2254327

KEYWORDS: Image segmentation, Blood vessels, Bone, Kidney, Heart, Surgery, Computed tomography, 3D image enhancement, 3D image processing, Spine, Natural surfaces

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Proceedings Article | 24 March 2016 Paper

Computer-aided diagnosis for osteoporosis using chest 3D CT images

K. Yoneda, M. Matsuhiro, H. Suzuki, Y. Kawata, N. Niki, Y. Nakano, H. Ohmatsu, M. Kusumoto, T. Tsuchida, K. Eguchi, M. Kaneko

Proceedings Volume 9785, 97853A (2016) https://doi.org/10.1117/12.2216600

KEYWORDS: Bone, Computer aided diagnosis and therapy, Computed tomography, Chest, 3D image processing, Dual energy x-ray absorptiometry, Spine, Algorithm development, Image analysis, Image resolution, Shape analysis

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Proceedings Article | 24 March 2016 Paper

Computer aided diagnosis for severity assessment of pneumoconiosis using CT images

Hidenobu Suzuki, Mikio Matsuhiro, Yoshiki Kawata, Noboru Niki, Katsuya Kato, Takumi Kishimoto, Kazuto Ashizawa

Proceedings Volume 9785, 978531 (2016) https://doi.org/10.1117/12.2217480

KEYWORDS: Lung, Computed tomography, Computer aided diagnosis and therapy, Image segmentation, Computing systems, Chest, Quantitative analysis

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Proceedings Article | 20 March 2015 Paper

Peripleural lung disease detection based on multi-slice CT images

M. Matsuhiro, H. Suzuki, Y. Kawata, N. Niki, Y. Nakano, H. Ohmatsu, M. Kusumoto, T. Tsuchida, K. Eguchi, M. Kaneko

Proceedings Volume 9414, 94142W (2015) https://doi.org/10.1117/12.2081718

KEYWORDS: Lung, Bone, X-ray computed tomography, Image segmentation, Computed tomography, 3D image processing, Medical imaging, Detection and tracking algorithms, Blood vessels, Medicine

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Proceedings Article | 20 March 2015 Paper

Quantitative assessment of smoking-induced emphysema progression in longitudinal CT screening for lung cancer

H. Suzuki, R. Mizuguchi, M. Matsuhiro, Y. Kawata, N. Niki, Y. Nakano, H. Ohmatsu, M. Kusumoto, T. Tsuchida, K. Eguchi, M. Kaneko, N. Moriyama

Proceedings Volume 9414, 94142O (2015) https://doi.org/10.1117/12.2082054

KEYWORDS: Emphysema, Computed tomography, Lung, Lung cancer, Image segmentation, Signal attenuation, Chronic obstructive pulmonary disease, Statistical analysis, Computer aided diagnosis and therapy, Cancer

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Proceedings Article | 18 March 2014 Paper

Longitudinal follow-up study of smoking-induced emphysema progression in low-dose CT screening of lung cancer

H. Suzuki, M. Matsuhiro, Y. Kawata, N. Niki, Y. Nakano, H. Ohmatsu, M. Kusumoto, T. Tsuchida, K. Eguchi, Masahiro Kaneko, N. Moriyama

Proceedings Volume 9035, 90352M (2014) https://doi.org/10.1117/12.2044007

KEYWORDS: Emphysema, Lung, Computed tomography, Lung cancer, Image segmentation, Chronic obstructive pulmonary disease, Signal attenuation, Spirometry, Statistical analysis, Computer aided diagnosis and therapy

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Proceedings Article | 28 February 2013 Paper

Extraction method of interlobar fissure based on multi-slice CT images

M. Matsuhiro, H. Suzuki, Y. Kawata, N. Niki, J. Ueno, Y. Nakano, E. Ogawa, S. Muro, M. Mishima, H. Ohmatsu, Noriyuki Moriyama

Proceedings Volume 8670, 867031 (2013) https://doi.org/10.1117/12.2007822

KEYWORDS: Lung, Gold, Computed tomography, Medicine, Cancer, Oncology, Lung cancer, Structural analysis, Detection and tracking algorithms, Data acquisition

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Proceedings Article | 26 February 2013 Paper

Blood vessel-based liver segmentation through the portal phase of a CT dataset

Ahmed Maklad, Mikio Matsuhiro, Hidenobu Suzuki, Yoshiki Kawata, Noboru Niki, Noriyuki Moriyama, Toru Utsunomiya, Mitsuo Shimada

Proceedings Volume 8670, 86700X (2013) https://doi.org/10.1117/12.2007546

KEYWORDS: Liver, Blood vessels, Tumors, Image segmentation, Natural surfaces, Blood, Medical imaging, Cancer, Liver cancer, Computer security

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Proceedings Article | 14 February 2012 Paper

Extraction of liver volumetry based on blood vessel from the portal phase CT dataset

Ahmed Maklad, Mikio Matsuhiro, Hidenobu Suzuki, Yoshiki Kawata, Noboru Niki, Tohru Utsunomiya, Mitsuo Shimada

Proceedings Volume 8314, 83142O (2012) https://doi.org/10.1117/12.911175

KEYWORDS: Liver, Blood vessels, Natural surfaces, Surgery, Computed tomography, Heart, Image segmentation, Bone, Kidney, Calcium

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Proceedings Article | 9 March 2011 Paper

Classification algorithm of lung lobe for lung disease cases based on multislice CT images

M. Matsuhiro, Y. Kawata, N. Niki, Y. Nakano, M. Mishima, H. Ohmatsu, T. Tsuchida, K. Eguchi, M. Kaneko, N. Moriyama

Proceedings Volume 7963, 796331 (2011) https://doi.org/10.1117/12.877997

KEYWORDS: Lung, Computed tomography, Lung cancer, Image classification, Blood vessels, 3D image processing, X-ray computed tomography, Medicine, Cancer, Image processing

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Proceedings Article | 30 March 2007 Paper

Classification algorithm of pulmonary vein and artery based on multi-slice CT image

Taihei Yonekura, Mikio Matsuhiro, Shinsuke Saita, Mitsuru Kubo, Yoshiki Kawata, Noboru Niki, Hiromu Nishitani, Hironobu Ohmatsu, Ryutaro Kakinuma, Noriyuki Moriyama

Proceedings Volume 6514, 65142E (2007) https://doi.org/10.1117/12.709857

KEYWORDS: Arteries, Veins, Lung, Blood vessels, Computed tomography, 3D image processing, Algorithm development, Image processing, X-ray computed tomography, Image classification

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Showing 5 of 25 publications

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