Dr. Hirohisa Oda Profile

Dr. Hirohisa Oda

at Univ. of Shizuoka

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Publications (23)

Proceedings Article | 2 April 2024 Presentation + Paper

Intestine segmentation from CT volume based on bidirectional teaching

Qin An, Hirohisa Oda, Yuichiro Hayashi, Takayuki Kitasaka, Akinari Hinoki, Hiroo Uchida, Kojiro Suzuki, Aitaro Takimoto, Masahiro Oda, Kensaku Mori

Proceedings Volume 12926, 129260Z (2024) https://doi.org/10.1117/12.3006623

KEYWORDS: Intestine, Image segmentation, Education and training, Convolution, Voxels, Plutonium, Semantics, Computed tomography, Medical imaging, Information science

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Proceedings Article | 3 April 2023 Presentation + Paper

L-former: a lightweight transformer for realistic medical image generation and its application to super-resolution

Tong Zheng, Hirohisa Oda, Yuichiro Hayashi, Shota Nakamura, Masaki Mori, Hirotsugu Takabatake, Hiroshi Natori, Masahiro Oda, Kensaku Mori

Proceedings Volume 12464, 1246415 (2023) https://doi.org/10.1117/12.2653776

KEYWORDS: Transformers, Medical imaging, Super resolution, Education and training, Wavelets, Voxels, Gallium nitride, Discrete wavelet transforms, Biomedical applications, Convolution

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SPIE Journal Paper | 5 April 2022 Open Access

SR-CycleGAN: super-resolution of clinical CT to micro-CT level with multi-modality super-resolution loss

Tong Zheng, Hirohisa Oda, Yuichiro Hayashi, Takayasu Moriya, Shota Nakamura, Masaki Mori, Hirotsugu Takabatake, Hiroshi Natori, Masahiro Oda, Kensaku Mori

JMI, Vol. 9, Issue 02, 024003, (April 2022) https://doi.org/10.1117/12.10.1117/1.JMI.9.2.024003

KEYWORDS: Computed tomography, Lawrencium, X-ray computed tomography, Lung, Super resolution, Lung cancer, Convolution, Image segmentation, Image resolution, Gallium nitride

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Purpose: We propose a super-resolution (SR) method, named SR-CycleGAN, for SR of clinical computed tomography (CT) images to the micro-focus x-ray CT CT (μCT) level. Due to the resolution limitations of clinical CT (about 500 × 500 × 500 μm3 / voxel), it is challenging to obtain enough pathological information. On the other hand, μCT scanning allows the imaging of lung specimens with significantly higher resolution (about 50 × 50 × 50 μm3 / voxel or higher), which allows us to obtain and analyze detailed anatomical information. As a way to obtain detailed information such as cancer invasion and bronchioles from preoperative clinical CT images of lung cancer patients, the SR of clinical CT images to the μCT level is desired. Approach: Typical SR methods require aligned pairs of low-resolution (LR) and high-resolution images for training, but it is infeasible to obtain precisely aligned paired clinical CT and μCT images. To solve this problem, we propose an unpaired SR approach that can perform SR on clinical CT to the μCT level. We modify a conventional image-to-image translation network named CycleGAN to an inter-modality translation network named SR-CycleGAN. The modifications consist of three parts: (1) an innovative loss function named multi-modality super-resolution loss, (2) optimized SR network structures for enlarging the input LR image to k2-times by width and height to obtain the SR output, and (3) sub-pixel shuffling layers for reducing computing time. Results: Experimental results demonstrated that our method successfully performed SR of lung clinical CT images. SSIM and PSNR scores of our method were 0.54 and 17.71, higher than the conventional CycleGAN’s scores of 0.05 and 13.64, respectively. Conclusions: The proposed SR-CycleGAN is usable for the SR of a lung clinical CT into μCT scale, while conventional CycleGAN output images with low qualitative and quantitative values. More lung micro-anatomy information could be observed to aid diagnosis, such as the shape of bronchioles walls.

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Proceedings Article | 4 April 2022 Poster + Presentation + Paper

Multi-class prediction for improving intestine segmentation on non-fecal-tagged CT volume

Hirohisa Oda, Yuichiro Hayashi, Takayuki Kitasaka, Aitaro Takimoto, Akinari Hinoki, Hiroo Uchida, Kojiro Suzuki, Masahiro Oda, Kensaku Mori

Proceedings Volume 12033, 120331J (2022) https://doi.org/10.1117/12.2611441

KEYWORDS: Intestine, Image segmentation, Computer aided diagnosis and therapy, Liquids, Computed tomography, Computer-aided diagnosis, Machine learning

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Proceedings Article | 4 April 2022 Presentation + Paper

Coarse-to-fine cascade framework for cross-modality super-resolution on clinical/micro CT dataset

Tong Zheng, Hirohisa Oda, Yuichiro Hayashi, Shota Nakamura, Masaki Mori, Hirotsugu Takabatake, Hiroshi Natori, Masahiro Oda, Kensaku Mori

Proceedings Volume 12032, 120321T (2022) https://doi.org/10.1117/12.2611311

KEYWORDS: Computed tomography, Lawrencium, Medical imaging, Lung, Image registration, Super resolution, Computer programming, Feature extraction, Scanners, Lutetium

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Proceedings Article | 15 February 2021 Presentation + Paper

Intestinal region reconstruction of ileus cases from 3D CT images based on graphical representation and its visualization

Hirohisa Oda, Yuichiro Hayashi, Takayuki Kitasaka, Yudai Tamada, Aitaro Takimoto, Akinari Hinoki, Hiroo Uchida, Kojiro Suzuki, Hayato Itoh, Masahiro Oda, Kensaku Mori

Proceedings Volume 11597, 115971N (2021) https://doi.org/10.1117/12.2581261

KEYWORDS: Intestine, Computer aided diagnosis and therapy, Visualization, Image segmentation, Computing systems

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Proceedings Article | 16 March 2020 Paper

Visualizing intestines for diagnostic assistance of ileus based on intestinal region segmentation from 3D CT images

Hirohisa Oda, Kohei Nishio, Takayuki Kitasaka, Hizuru Amano, Aitaro Takimoto, Hiroo Uchida, Kojiro Suzuki, Hayato Itoh, Masahiro Oda, Kensaku Mori

Proceedings Volume 11314, 1131434 (2020) https://doi.org/10.1117/12.2548910

KEYWORDS: Intestine, Image segmentation, Visualization, Computed tomography, Convolution, Diagnostics, 3D image processing, Human-machine interfaces, Virtual colonoscopy

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SPIE Journal Paper | 11 March 2020 Open Access

Cardiac fiber tracking on super high-resolution CT images: a comparative study

Hirohisa Oda, Holger Roth, Takaaki Sugino, Naoki Sunaguchi, Noriko Usami, Masahiro Oda, Daisuke Shimao, Shu Ichihara, Tetsuya Yuasa, Masami Ando, Toshiaki Akita, Yuji Narita, Kensaku Mori

JMI, Vol. 7, Issue 02, 026001, (March 2020) https://doi.org/10.1117/12.10.1117/1.JMI.7.2.026001

KEYWORDS: X-ray computed tomography, Computed tomography, Heart, X-rays, Statistical analysis, Visualization, Tissues, Structured optical fibers, Scanners, Bioalcohols

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Proceedings Article | 10 March 2020 Presentation + Paper

Multi-modality super-resolution loss for GAN-based super-resolution of clinical CT images using micro CT image database

Tong Zheng, Hirohisa Oda, Takayasu Moriya, Takaaki Sugino, Shota Nakamura, Masahiro Oda, Masaki Mori, Hirotsugu Takabatake, Hiroshi Natori, Kensaku Mori

Proceedings Volume 11313, 1131305 (2020) https://doi.org/10.1117/12.2548929

KEYWORDS: Computed tomography, Super resolution, Lung cancer, Lung, Lawrencium, Image resolution, Databases, Cancer, Information science, Image processing

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Proceedings Article | 27 March 2019 Paper

Investigation of extracting interlobular septa with Hessian analysis and radial structure tensor combined with roundness error in micro-CT volume

Xiaotian Zhao, Hirohisa Oda, Shota Nakamura, Yuichiro Hayashi, Hayato Itoh, Masahiro Oda, Kensaku Mori

Proceedings Volume 11050, 110501E (2019) https://doi.org/10.1117/12.2521646

KEYWORDS: Lung, Error analysis, Tissues, Lung cancer, Visualization, Blood vessels, Information science, Binary data, Nondestructive evaluation, Computed tomography

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Proceedings Article | 15 March 2019 Presentation + Paper

Improving V-Nets for multi-class abdominal organ segmentation

Chen Shen, Fausto Milletari, Holger Roth, Hirohisa Oda, Masahiro Oda, Yuichiro Hayashi, Kazunari Misawa, Kensaku Mori

Proceedings Volume 10949, 109490B (2019) https://doi.org/10.1117/12.2512790

KEYWORDS: Image segmentation, 3D image processing, Data modeling, Medical imaging, Computed tomography, Image processing, Arteries, Veins, 3D modeling, Network architectures

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Proceedings Article | 15 March 2019 Presentation + Paper

Unsupervised segmentation of micro-CT images based on a hybrid of variational inference and adversarial learning

Takayasu Moriya, Holger Roth, Shota Nakamura, Hirohisa Oda, Masahiro Oda, Kensaku Mori

Proceedings Volume 10953, 109530L (2019) https://doi.org/10.1117/12.2513094

KEYWORDS: Image segmentation, Computer programming, Lung cancer, 3D image processing, Tissues, Feature extraction, Machine learning

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Proceedings Article | 15 March 2019 Presentation + Paper

Scanning, registration, and fiber estimation of rabbit hearts using micro-focus and refraction-contrast x-ray CT

Hirohisa Oda, Holger Roth, Takaaki Sugino, Naoki Sunaguchi, Noriko Usami, Masahiro Oda, Daisuke Shimao, Shu Ichihara, Tetsuya Yuasa, Masami Ando, Toshiaki Akita, Yuji Narita, Kensaku Mori

Proceedings Volume 10953, 109531I (2019) https://doi.org/10.1117/12.2512145

KEYWORDS: Heart, X-ray computed tomography, X-ray imaging, Cardiac imaging, Imaging systems, 3D microstructuring, Cardiology, Phase contrast

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Proceedings Article | 13 March 2019 Paper

Lung segmentation based on a deep learning approach for dynamic chest radiography

Yuki Kitahara, Rie Tanaka, Holger Roth, Hirohisa Oda, Kensaku Mori, Kazuo Kasahara, Isao Matsumoto

Proceedings Volume 10950, 109503M (2019) https://doi.org/10.1117/12.2512711

KEYWORDS: Lung, Image segmentation, Chest, Radiography, Chest imaging, Surgery, Gold, Health sciences, Medicine, Cardiovascular surgery

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Proceedings Article | 1 March 2019 Paper

Dynamic chest radiography for pulmonary function diagnosis: A validation study using 4D extended cardiac-torso (XCAT) phantom

Rie Tanaka, Ehsan Samei, Paul Segars, Ehsan Abadi, Holger Roth, Hirohisa Oda, Kensaku Mori

Proceedings Volume 10948, 109483I (2019) https://doi.org/10.1117/12.2512332

KEYWORDS: Optical spheres, Lung, Chest, Radiography, Tissues, Image segmentation, Chest imaging, Heart, Emphysema, X-rays

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Proceedings Article | 12 March 2018 Paper

Unsupervised segmentation of 3D medical images based on clustering and deep representation learning

Takayasu Moriya, Holger Roth, Shota Nakamura, Hirohisa Oda, Kai Nagara, Masahiro Oda, Kensaku Mori

Proceedings Volume 10578, 1057820 (2018) https://doi.org/10.1117/12.2293414

KEYWORDS: Image segmentation, Medical imaging, 3D image processing, Machine learning, Tissues, 3D acquisition, Convolution, Lung cancer, Information science

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Proceedings Article | 6 March 2018 Paper

Unsupervised pathology image segmentation using representation learning with spherical k-means

Takayasu Moriya, Holger Roth, Shota Nakamura, Hirohisa Oda, Kai Nagara, Masahiro Oda, Kensaku Mori

Proceedings Volume 10581, 1058111 (2018) https://doi.org/10.1117/12.2292172

KEYWORDS: Image segmentation, Pathology, Feature extraction, Lung cancer, Lung, Visualization, Image visualization, Machine learning

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Proceedings Article | 2 March 2018 Presentation + Paper

Towards dense volumetric pancreas segmentation in CT using 3D fully convolutional networks

Holger Roth, Masahiro Oda, Natsuki Shimizu, Hirohisa Oda, Yuichiro Hayashi, Takayuki Kitasaka, Michitaka Fujiwara, Kazunari Misawa, Kensaku Mori

Proceedings Volume 10574, 105740B (2018) https://doi.org/10.1117/12.2293499

KEYWORDS: Machine learning, Pancreas, Image segmentation, 3D image processing, Computed tomography, Image processing, 3D modeling, Network architectures, Convolution, Data modeling, Information science

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Proceedings Article | 27 February 2018 Paper

Dense volumetric detection and segmentation of mediastinal lymph nodes in chest CT images

Hirohisa Oda, Holger Roth, Kanwal Bhatia, Masahiro Oda, Takayuki Kitasaka, Shingo Iwano, Hirotoshi Homma, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Julia Schnabel, Kensaku Mori

Proceedings Volume 10575, 1057502 (2018) https://doi.org/10.1117/12.2287066

KEYWORDS: Lymphatic system, Image segmentation, Chest, Computed tomography, Lung, Lung cancer, Arteries, 3D image processing, Target detection

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SPIE Journal Paper | 9 November 2017 Open Access

Automated mediastinal lymph node detection from CT volumes based on intensity targeted radial structure tensor analysis

Hirohisa Oda, Kanwal K. Bhatia, Masahiro Oda, Takayuki Kitasaka, Shingo Iwano, Hirotoshi Homma, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Julia Schnabel, Kensaku Mori

JMI, Vol. 4, Issue 04, 044502, (November 2017) https://doi.org/10.1117/12.10.1117/1.JMI.4.4.044502

KEYWORDS: Lymphatic system, Target detection, Detection and tracking algorithms, Computed tomography, Optical spheres, Lung, Digital filtering, Image segmentation, Chest, Lung cancer

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Proceedings Article | 13 March 2017 Presentation + Paper

Extracellular matrix directions estimation of the heart on micro-focus x-ray CT volumes

Hirohisa Oda, Masahiro Oda, Takayuki Kitasaka, Toshiaki Akita, Kensaku Mori

Proceedings Volume 10137, 101370M (2017) https://doi.org/10.1117/12.2254949

KEYWORDS: 3D microstructuring, Pathology, Heart, Cardiac imaging, Image segmentation, X-rays, Image processing, Visualization, Tissues, Diffusion, Computed tomography

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Proceedings Article | 3 March 2017 Presentation + Paper

Hessian-assisted supervoxel: structure-oriented voxel clustering and application to mediastinal lymph node detection from CT volumes

Hirohisa Oda, Kanwal Bhatia, Masahiro Oda, Takayuki Kitasaka, Shingo Iwano, Hirotoshi Homma, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Julia Schnabel, Kensaku Mori

Proceedings Volume 10134, 101341D (2017) https://doi.org/10.1117/12.2254782

KEYWORDS: Lymphatic system, Image segmentation, Feature extraction, Chest, Computer-aided diagnosis, Lung cancer, Lung, Image processing algorithms and systems, Blood vessels, Esophagus, Target detection, Information science, Computer aided diagnosis and therapy

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Proceedings Article | 24 March 2016 Paper

Intensity targeted radial structure tensor analysis and its application for automated mediastinal lymph node detection from CT volumes

Hirohisa Oda, Yukitaka Nimura, Masahiro Oda, Takayuki Kitasaka, Shingo Iwano, Hirotoshi Honma, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Kensaku Mori

Proceedings Volume 9785, 97850E (2016) https://doi.org/10.1117/12.2216663

KEYWORDS: Lymphatic system, Target detection, Machine learning, Computer aided diagnosis and therapy, Lung cancer, Chest, Image filtering, Optical spheres, Solids, Tissues, Image segmentation, Binary data

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Showing 5 of 23 publications

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