Faculty Profiles - MORI, Kensaku

Papers - MORI, Kensaku

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Virtual cleansing by unpaired image translation of intestines for detecting obstruction Reviewed

K. Nishio, H. Oda, T. Kitasaka, Y. Tamada, H. Amano, A. Takimoto, K. Chiba, Y. Hayashi, H. Itoh, M. Oda, A. Hinoki, H. Uchida, K. Mori

International Journal of Computer Assisted Radiology and Surgery Vol. 15 ( 1 ) page： S21 - S22 2020.6

TinyLoss: loss function for tiny image difference evaluation and its application to unpaired non-contrast to contrast abdominal CT estimation Reviewed

M. Oda, T. Hu, K. K. Kumamaru, T. Akashi, S. Aoki, K. Mori

International Journal of Computer Assisted Radiology and Surgery Vol. 15 ( 1 ) page： S25 - S26 2020.6

SR-CycleGAN V2: CycleGAN-based unsupervised superresolution with pixel-shuffling Reviewed

T. Zheng, H. Oda, T. Moriya, T. Sugino, S. Nakamura, M. Oda, M. Mori, H. Takabatake, H. Natori, K. Mori

International Journal of Computer Assisted Radiology and Surgery Vol. 15 ( 1 ) page： S27 - S28 2020.6

Blood vessel segmentation from laparoscopic video using ConvLSTM U-Net

S. Morimitsu, S. Yamamoto, T. Ozawa, T. Kitasaka, Y. Hayashi, M. Oda, M. Ito, N. Takeshita, K. Misawa, K. Mori

International Journal of Computer Assisted Radiology and Surgery Vol. 15 ( 1 ) page： S63 - S64 2020.6

Extraction of blood vessel regions in liver from CT volumes using fully convolutional networks for computer assisted liver surgery Reviewed

Y. Hayashi, C. Shen, T. Igami, M. Nagino, K. Mori

International Journal of Computer Assisted Radiology and Surgery Vol. 15 ( 1 ) page： S152 - S153 2020.6

AIによるSSA/Pの超拡大内視鏡診断 Invited Reviewed

小川悠史, 工藤進英, 森悠一, 三澤将史, 片岡伸一, 前田康晴, 一政克朗, 石垣智之, 工藤豊樹, 若村邦彦, 林武雅, 馬場俊之, 石田文生, 伊東隼人, 小田昌宏, 森健策

日本大腸検査学会雑誌 Vol. 36 ( 2 ) page： 125 - 125 2020.5

バーチャル・リアリティ手術シュミレーター（VRS）の意義と今後の展望

藤原道隆, 林雄一郎, 高見秀樹, 田中千恵, 森健策, 小寺泰弘

臨床外科 Vol. 75 ( 4 ) page： 476 - 482 2020.4

Cardiac fiber tracking on super high-resolution CT images: a comparative study. Invited International journal

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

Journal of medical imaging (Bellingham, Wash.) Vol. 7 ( 2 ) page： 026001 - 026001 2020.3

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

Purpose: High-resolution cardiac imaging and fiber analysis methods are required to understand cardiac anatomy. Although refraction-contrast x-ray CT (RCT) has high soft tissue contrast, it cannot be commonly used because it requires a synchrotron system. Microfocus x-ray CT ( μ CT ) is another commercially available imaging modality. Approach: We evaluate the usefulness of μ CT for analyzing fibers by quantitatively and objectively comparing the results with RCT. To do so, we scanned a rabbit heart by both modalities with our original protocol of prepared materials and compared their image-based analysis results, including fiber orientation estimation and fiber tracking. Results: Fiber orientations estimated by two modalities were closely resembled under the correlation coefficient of 0.63. Tracked fibers from both modalities matched well the anatomical knowledge that fiber orientations are different inside and outside of the left ventricle. However, the μ CT volume caused incorrect tracking around the boundaries caused by stitching scanning. Conclusions: Our experimental results demonstrated that μ CT scanning can be used for cardiac fiber analysis, although further investigation is required in the differences of fiber analysis results on RCT and μ CT .

DOI： 10.1117/1.JMI.7.2.026001

3Dプリンティングの最新動向 Invited

森　健策

インナービジョン Vol. 35 ( 2 ) page： 36-37 2020.2

Spatial information-embedded fully convolutional networks for multi-organ segmentation with improved data augmentation and instance normalization Reviewed

Chen Shen, Chenglong Wang, Holger R. Roth, Masahiro Oda, Yuichiro Hayashi, Kazunari Misawa, Kensaku Mori

Medical Imaging 2020: Image Processing Vol. 11313 2020.2

Usefulness of fine-tuning for deep learning based multi-organ regions segmentation method from non-contrast CT volumes using small training dataset Reviewed

Yuichiro Hayashi, Chen Shen, Holger R. Roth, Masahiro Oda, Kazunari Misawa, Masahiro Jinzaki, Masahiro Hashimoto, Kanako K. Kumamaru, Shigeki Aoki, Kensaku Mori