Faculty Profiles - MORI, Kensaku

Papers - MORI, Kensaku

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Automated ganglion cell detection using fully convolutional networks and evaluation under different training losses

Hirohisa Oda, Kosuke Chiba, Holger R. Roth, Takayuki Kitasaka, Masahiro Oda, Akinari Hinoki, Hiroo Uchida, Kensaku Mori

International Journal of Computer Assisted Radiology and Surgery Vol. 13 ( 1 ) page：ｓ104-106 2018.6

Semi-supervised spherical K-means for segmenting idiopathic interstitial pneumonia from chest CT images

C. Wang, T. Moriya, Y. Hayashi, M. Oda, H. Ohkubo, K. Mori

International Journal of Computer Assisted Radiology and Surgery Vol. 13 ( 1 ) page：ｓ27-28 2018.6

Evaluation of 3D fully convolutional networks for multi-class organ segmentation in contrast-enhanced CT

Chen Shen, Holger R. Roth, Hirohisa Oda, Masahiro Oda, Yuichiro Hayashi, Kazunari Misawa, Tadaaki Miyamoto, and Kensaku Mori

International Journal of Computer Assisted Radiology and Surgery Vol. 13 ( 1 ) page：ｓ21-22 2018.6

Abdominal artery segmentation from CT volumes using fully convolutional network for small artery segmentation

Masahiro Oda, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Kensaku Mori,

International Journal of Computer Assisted Radiology and Surgery Vol. 13 ( 1 ) page：ｓ20-21 2018.6

Auto-context 3D fully convolutional networks for multi-scale semantic segmentation of abdominal CT volumes

K. Mori, H. Roth, C. Shen, H. Oda, T. Sugino, M. Oda, Y. Hayashi, K. Misawa

International Journal of Computer Assisted Radiology and Surgery Vol. 13 ( 1 ) page：ｓ18-19 2018.6

Unsupervised 3D micro-CT image segmentation based on a hybrid of VAE and GAN

T. Moriya, H. Roth, S. Nakamura, H. Oda, K. Nagara, M. Oda, K. Mori

International Journal of Computer Assisted Radiology and Surgery Vol. 13 ( 1 ) page：ｓ15-17 2018.6

Abdominal artery segmentation from CT volumes using fully convolutional network for small artery segmentation

Masahiro Oda, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Kensaku Mori

International Journal of Computer Assisted Radiology and Surgery Vol. 13 ( 1 ) page： s20-21 2018.6

Automated ganglion cell detection using fully convolutional networks and evaluation under different training losses

Hirohisa Oda, Kosuke Chiba, Holger R. Roth, Takayuki Kitasaka, Masahiro Oda, Akinari Hinoki, Hiroo Uchida, Kensaku Mori

International Journal of Computer Assisted Radiology and Surgery Vol. 13 ( 1 ) page： s104-106 2018.6

Auto-context 3D fully convolutional networks for multi-scale semantic segmentation of abdominal CT volumes

K. Mori, H. Roth, C. Shen, H. Oda, T. Sugino, M. Oda, Y. Hayashi, K. Misawa

International Journal of Computer Assisted Radiology and Surgery Vol. 13 ( 1 ) page： s18-19 2018.6

Evaluation of 3D fully convolutional networks for multi-class organ segmentation in contrast-enhanced CT

Chen Shen, Holger R. Roth, Hirohisa Oda, Masahiro Oda, Yuichiro Hayashi, Kazunari Misawa, Tadaaki Miyamoto, Kensaku Mori

International Journal of Computer Assisted Radiology and Surgery Vol. 13 ( 1 ) page： s21-22 2018.6

Unsupervised 3D micro-CT image segmentation based on a hybrid of VAE and GAN

T. Moriya, H. Roth, S. Nakamura, H. Oda, K. Nagara, M. Oda, K. Mori

International Journal of Computer Assisted Radiology and Surgery Vol. 13 ( 1 ) page： s15-17 2018.6

Semi-supervised spherical K-means for segmenting idiopathic interstitial pneumonia from chest CT images

C. Wang, T. Moriya, Y. Hayashi, M. Oda, H. Ohkubo, K. Mori

International Journal of Computer Assisted Radiology and Surgery Vol. 13 ( 1 ) page： s27-28 2018.6

Improvement of robustness of SLAM-based bronchoscope tracking by posture guided feature matching

Cheng Wang, Masahiro Oda, Yuichiro Hayashi, Hirotoshi Honma, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Kensaku Mori

International Journal of Computer Assisted Radiology and Surgery Vol. 13 ( 1 ) page： s11-12 2018.6

Eye structure segmentation on micro-CT images using 3D fully convolutional network with sparsely-annotated training data

T. Sugino, H. Roth, M. Oda, S. Omata, S. Sakuma, F. Arai, K. Mori

International Journal of Computer Assisted Radiology and Surgery Vol. 13 ( 1 ) page： s182-184 2018.6

Artificial Intelligence-Assisted Polyp Detection for Colonoscopy: Initial Experience. Reviewed International journal Open Access

Masashi Misawa, Shin-Ei Kudo, Yuichi Mori, Tomonari Cho, Shinichi Kataoka, Akihiro Yamauchi, Yushi Ogawa, Yasuharu Maeda, Kenichi Takeda, Katsuro Ichimasa, Hiroki Nakamura, Yusuke Yagawa, Naoya Toyoshima, Noriyuki Ogata, Toyoki Kudo, Tomokazu Hisayuki, Takemasa Hayashi, Kunihiko Wakamura, Toshiyuki Baba, Fumio Ishida, Hayato Itoh, Holger Roth, Masahiro Oda, Kensaku Mori

Gastroenterology Vol. 154 ( 8 ) page： 2027 - + 2018.6

An application of cascaded 3D fully convolutional networks for medical image segmentation Reviewed Open Access

Holger R. Roth, Hirohisa Oda, Xiangrong Zhou, Natsuki Shimizu, Ying Yang, Yuichiro Hayashi, Masahiro Oda, Michitaka Fujiwara, Kazunari Misawa, Kensaku Mori

Computerized Medical Imaging and Graphics Vol. 66 page： 90 - 99 2018.6

Language：English Publishing type：Research paper (scientific journal) Publisher：Elsevier Ltd

Recent advances in 3D fully convolutional networks (FCN) have made it feasible to produce dense voxel-wise predictions of volumetric images. In this work, we show that a multi-class 3D FCN trained on manually labeled CT scans of several anatomical structures (ranging from the large organs to thin vessels) can achieve competitive segmentation results, while avoiding the need for handcrafting features or training class-specific models. To this end, we propose a two-stage, coarse-to-fine approach that will first use a 3D FCN to roughly define a candidate region, which will then be used as input to a second 3D FCN. This reduces the number of voxels the second FCN has to classify to ∼10% and allows it to focus on more detailed segmentation of the organs and vessels. We utilize training and validation sets consisting of 331 clinical CT images and test our models on a completely unseen data collection acquired at a different hospital that includes 150 CT scans, targeting three anatomical organs (liver, spleen, and pancreas). In challenging organs such as the pancreas, our cascaded approach improves the mean Dice score from 68.5 to 82.2%, achieving the highest reported average score on this dataset. We compare with a 2D FCN method on a separate dataset of 240 CT scans with 18 classes and achieve a significantly higher performance in small organs and vessels. Furthermore, we explore fine-tuning our models to different datasets. Our experiments illustrate the promise and robustness of current 3D FCN based semantic segmentation of medical images, achieving state-of-the-art results.1

DOI： 10.1016/j.compmedimag.2018.03.001

Port placement planning method for assistant surgeon in laparoscopic gastrectomy

Y. Hayashi, K. Misawa, K. Mori

International Journal of Computer Assisted Radiology and Surgery Vol. 13 ( 1 ) page： s231-232 2018.6

Port placement planning method for assistant surgeon in laparoscopic gastrectomy

Y. Hayashi, K. Misawa, K. Mori

International Journal of Computer Assisted Radiology and Surgery Vol. 13 ( 1 ) page： s231-232 2018.6

デスクトップ型マイクロCTによる微細解剖構造イメージング Open Access

森健策

Medical Imaging Technology Vol. 36 ( 3 ) page： 127-132 2018.5

特集/マイクロ解剖学のための微細解剖構造イメージング Open Access

森健策

Medical Imaging Technology Vol. 36 ( 3 ) page： 105-106 2018.5

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Papers - MORI, Kensaku