Faculty Profiles - MORI, Kensaku

Papers - MORI, Kensaku

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A study on improvement of airway segmentation using Hybrid method Invited Reviewed

Qier, M; Kitasaka, T; Nimura, Y; Oda, M; Mori, K

PROCEEDINGS 3RD IAPR ASIAN CONFERENCE ON PATTERN RECOGNITION ACPR 2015 page： 549 - 553 2015

Connection method of separated luminal regions of intestine from CT volumes Invited Reviewed

Oda Masahiro, Kitasaka Takayuki, Furukawa Kazuhiro, Watanabe Osamu, Ando Takafumi, Hirooka Yoshiki, Goto Hidemi, Mori Kensaku

MEDICAL IMAGING 2015: COMPUTER-AIDED DIAGNOSIS Vol. 9414 2015

Development of a new detection device using a glass clip emitting infrared fluorescence for laparoscopic surgery of gastric cancer Invited Reviewed Open Access

Inada Shunko Albano, Fuchi Shingo, Mori Kensaku, Hasegawa Junichi, Misawa Kazunari, Nakanishi Hayao

6TH INTERNATIONAL CONFERENCE ON OPTICAL, OPTOELECTRONIC AND PHOTONIC MATERIALS AND APPLICATIONS (ICOOPMA) 2014 Vol. 619 2015

Development and clinical application of surgical navigation system for laparoscopic hepatectomy Invited Reviewed

Hayashi Yuichiro, Igami Tsuyoshi, Hirose Tomoaki, Nagino Masato, Mori Kensaku

MEDICAL IMAGING 2015: IMAGE-GUIDED PROCEDURES, ROBOTIC INTERVENTIONS, AND MODELING Vol. 9415 2015

YOLOv5 Attention Analysis for Anterior Eye Disease Classification: Grad-CAM++ Feature Importance and Cut-and-Paste Validation Invited Reviewed

Yoshiyuki Kitaguchi, Yuta Ueno, Takefumi Yamaguchi, Hiroki Maehara, Dai Miyazaki, Ryohei Nejima, Takenori Inomata, Naoko Kato, Tai-ichiro Chikama, Jun Ominato, Tatsuya Yunoki, Kinya Tsubota, Masahiro Oda, Kensaku Mori, Yu Yoshinaga, Rikako Iwasaki, Kohji Nishida, Tetsuro Oshika

Journal of Imaging Informatics in Medicine 2025.10

Enforcing Geometric Constraints of Surface Normal and Pose for Self-supervised Monocular Depth Estimation on Laparoscopic Image Invited Reviewed

Wenda Li, Yuichiro Hayashi, Masahiro Oda, Takayuki Kitasaka, Kazunari Misawa Kensaku Mori

LNCS15968 2025.9

Long-term impact of computer-aided adenoma detection: a prospective observational study Invited Reviewed

Taishi Okumura, Shin-Ei Kudo, Yutaro Ide, Shun Kato, Yuki Miyata, Kazumi Takisima, Yuki Takashina, Yosuke Minegishi, Masahiro Abe, Tatsuya Sakurai, Yuta Koyama, Kazuki Kato, Yasuharu Maeda, Yushi Ogawa, Katsuro Ichimasa, Noriyuki Ogata, Takemasa Hayashi, Kunihiko Wakamura, Toshiyuki Baba, Tetsuo Nemoto, Hideyuki Miyachi, Hayato Itoh, Masahiro Oda, Kensaku Mori, Masashi Misawa

Endoscopy 2025.9

Adaptive sensitivity-fisher regularization for heterogeneous transfer learning of vascular segmentation in laparoscopic videos Reviewed Open Access

Xinkai Zhao, Yuichiro Hayashi, Masahiro Oda, Takayuki Kitasaka, Kazunari Misawa, Kensaku Mori

International Journal of Computer Assisted Radiology and Surgery Vol. 20 ( 7 ) page： 1503 - 1511 2025.7

Language：English Publishing type：Research paper (scientific journal) Publisher：Springer Science and Business Media LLC

Abstract

Purpose

This study aims to enhance surgical safety by developing a method for vascular segmentation in laparoscopic surgery videos with limited visibility. We introduce an adaptive sensitivity-fisher regularization (ASFR) approach to adapt neural networks, initially trained on non-medical datasets, for vascular segmentation in laparoscopic videos.

Methods

Our approach utilizes heterogeneous transfer learning by integrating fisher information and sensitivity analysis to mitigate catastrophic forgetting and overfitting caused by limited annotated data in laparoscopic videos. We calculate fisher information to identify and preserve critical model parameters while using sensitivity measures to guide adjustment for new task.

Results

The fine-tuned models demonstrated high accuracy in vascular segmentation across various complex video sequences, including those with obscured vessels. For both invisible and visible vessels, our method achieved an average Dice score of 41.3. In addition to outperforming traditional transfer learning approaches, our method exhibited strong adaptability across multiple advanced video segmentation architectures.

Conclusion

This study introduces a novel heterogeneous transfer learning approach, ASFR, which significantly enhances the precision of vascular segmentation in laparoscopic videos. ASFR effectively addresses critical challenges in surgical image analysis and paves the way for broader applications in laparoscopic surgery, promising improved patient outcomes and increased surgical efficiency.

DOI： 10.1007/s11548-025-03404-2

Open Access

Scopus

PubMed

Other Link： https://link.springer.com/article/10.1007/s11548-025-03404-2/fulltext.html

SemiOrth: A novel orthogonal dual network architecture for enhanced semi-supervised medical image segmentation Invited Reviewed

Luyang Zhang, Masahiro Oda, Kensaku Mori

proc.SPIE Vol. 13406 2025.4

Enhanced sequential picking strategy with hyperparameter optimization for efficient surgical phase recognition Invited Reviewed

Guannan Yao, Yuichiro Hayashi, Masahiro Oda, Kazunari Misawa, Kensaku Mori

proc.SPIE Vol. 13408 2025.4

Content-consistent adaptation network for substantia nigra segmentation in cross-modalities and -datasets scenarios without retraining Invited Reviewed

Tao Hu, Hayato Itoh, Masahiro Oda, Shinji Saiki, Nobutaka Hattori, Koji Kamagata, Wataru Sako, Kei-ichi Ishikawa, Shigeki Aoki, Kensaku Mori

proc.SPIE Vol. 13406 2025.4

Estimation of hidden blood vessel locations in laparoscopic videos by combining preoperative and intraoperative information Invited Reviewed

Keigo Enomoto, Yuichiro Hayashi, Kazunari Misawa, Takayuki Kitasaka, Masahiro Oda, Kensaku Mori

proc.SPIE Vol. 13408 2025.4

Uncertainty-aware semi-supervised learning for enhanced multi-organ segmentation in CT volumes Invited Reviewed

Guotai Dong, Masahiro Oda, Yuichiro Hayashi, Kensaku Mori, Kazunari Misawa

proc.SPIE Vol. 13406 2025.4

Automated skill evaluation method for surgical images using optical flow and attention mechanism Invited Reviewed

Yuxuan Feng, Yuichiro Hayashi, Masahiro Oda, Takayuki Kitasaka, Akihiro Yasui, Chiyoe Shirota, Hiroo Uchida, Kensaku Mori

proc.SPIE Vol. 13408 2025.4

Prior knowledge-based blood vessel simulation and thrombus visualization using confocal laser scanning microscopic images Invited Reviewed

Cheng Wang, Yuichiro Hayashi, Masahiro Oda, Shuntaro Kawamura, Takanori Takebe, Kensaku Mori

proc.SPIE Vol. 13410 2025.4

WPDM: Enhancing subarachnoid hemorrhage CT detection with Worley-Perlin noise diffusion on imbalanced data Invited Reviewed

Zhongyang Lu, Tao Hu, Masahiro Oda, Yuichiro Hayashi, Takeyuki Watadani, Kensaku Mori

proc.SPIE Vol. 13407 2025.4

An Investigation of Labeled Data Ratio in Uncertainty-Aware Semi-Supervised Learning for Multi-Organ Segmentation Invited Reviewed

Guotai Dong, Masahiro Oda, Yuichiro Hayashi, Kazunari Misawa, Kensaku Mori

Vol. 124 ( 448 ) page： 17 - 20 2025.3

深層学習を用いた大腸内視鏡運動推定の定量評価 Invited Reviewed

小野坂捺, 伊東隼人, 小田昌宏, 三澤将史, 森　悠一, 工藤進英森健策

電子情報通信学会技術研究報告(MI), 信学技報 Vol. 123 ( 448 ) page： 94 - 97 2025.3

Bidirectional teaching between lightweight multi-view networks for intestine segmentation from CT volume Invited Reviewed

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

Journal of Medical Imaging Vol. 12 ( 2 ) 2025.3

Development of a YOLOv3-Based Model for Automated Detection of Thoracic Ossification of the Posterior Longitudinal Ligament and the Ligamentum Flavum on Plain Radiographs Invited Reviewed

Sadayuki Ito, Hiroaki Nakashima, Naoki Segi, Jun Ouchida, Ippei Yamauchi, Takashi Hirai, Masahiro Oda, Kensaku Mori, Masashi Yamazaki, Toshitaka Yoshii, Shiro Imagama

Journal of Clinical Medicine Vol. 14 ( 7 ) 2025.3

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Papers - MORI, Kensaku