Prof. Hiroo Uchida Profile

Prof. Hiroo Uchida

at Nagoya Univ Graduate School of Medicine

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Author

Publications (4)

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 | 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 | 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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