Ryoma Bise

Researches

News

    2024/8：One paper has been accepted in WACV2025 (Core Rank A, acceptance rate in Round 1:12% (167/1381))に採択されました。
    　　 Kaito Shiku, Kazuya Nishimura, Daiki Suehiro, Kiyohito Tanaka, and Ryoma Bise
    　　 Ordinal Multiple-instance Learning for Ulcerative Colitis Severity Estimation with Selective Aggregated Transformer
    2024/7：One paper has been accepted in BMVC2024 (Core Rank A, acceptance rate:25.8% (264/1020) )
    　　 Tatsuhiro Eguchi, Shumpei Takezaki, Mihoko Shimano, Takayuki Yagi, and Ryoma Bise
    　　 Guidance-base Diffusion Models for Improving Photoacoustic Image Quality
    2024/7：One paper has been accepted in ECAI2024 (Core Rank A, acceptance rate:23% (547/2344) )
    　　 Shunsuke Kubo, Shinnosuke Matsuo, Daiki Suehiro, Kazuhiro Terada, Hiroaki Ito, Akihiko Yoshizawa and Ryoma Bise
    　　 Theoretical Proportion Label Perturbation for Learning from Label Proportions in Large Bags
    2024/7：One paper has been accepted in MedIA (IF:10.7, top journal in medical image analysis)
    　　 Takeaki Kadota, Hideaki Hayashi, Ryoma Bise, Kiyohito Tanaka, and Seiichi Uchida
    　　 Deep Bayesian Active Learning-to-Rank with Relative Annotation for Estimation of Ulcerative Colitis Severity
    2024/5/14：A paper is accepted in MICCAI2024(Top Conference in Medical image analysis, acceptance rate:11%).
    　　 1. S. Matsuo, D. Suehiro, S. Uchida, H. Ito, K. Terada, A. Yoshizawa and R. Bise
    　　 Learning from Partial Label Proportions for Whole Slide Image Segmentation
    　　 International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI),2024
    2024/5/14：A paper is accepted in Nature Communications(Top Journal, IF:17.7).
    　　 1. K. Tomimatsu, T. Fujii, R. Bise, et al.,
    　　 Precise immunofluorescence canceling for highly multiplexed imaging to capture specific cell states
    　　 Nature Communications, 15, 1, 3657, 2024
    2023/6/24：One paper is accepted in ICASSP2024(Top Conference in Signal Processing).
    　　 1. Kaito Shiku, Shinnosuke Matsuo, Daiki Suehiro, and Ryoma Bise
    　　 Counting Network for Learning from Majority Label
    IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2024),2024
    2023/12/1：I am promoted to a Professor.
    2023/7/20：One paper is accepted in ICCV2023(Top Conference in Computer Vision).
    　　 1. Takanori Asanomi, Shinnosuke Matsuo, Daiki Suehiro and Ryoma Bise
    　　 MixBag: Bag-Level Data Augmentation for Learning from Label Proportions
    International Conference on Computer Vision (ICCV),2023
    2023/6/24：One paper is accepted in MICCAI2023(Top Conference in Medical image analysis).
    　　 1. Kazuya Nishimura, Ami Katanaya, Shinichiro Chuma, and Ryoma Bise
    　　 Mitosis Detection from Partial Annotation by Dataset Generation via Frame-Order Flipping
    2023/6/4：One paper is accepted in ICASSP2023(Top Conference in signal processing).
    　　 1. Shinnosuke Matsuo, Ryoma Bise, Seiichi Uchida, and Daiki Suehiro
    　　 Learning From Label Proportion with Online Pseudo-Label Decision by Regret Minimization
    2023/4/11：Four papers have been accepted in IEEE ISBI2023(h5-index:55).
    　　 1. Yuki Shigeyasu, Shota Harada, Kengo Araki, Akihiko Yoshizawa, Kazuhiro Terada, and Ryoma Bise
    　　 Spatial Distribution-based Pseudo Labeling for Pathological Image Segmentation
    　　 2. Xiaoqing Liu, Kengo Araki, Shota Harada, Akihiko Yoshizawa, Kazuhiro Terada, Mariyo Kurata, Naoki Nakajima, Hiroyuki Abe, Tetsuo Ushiku, and Ryoma Bise
    　　 Cluster Entropy: Active Domain Adaptation in Pathological Image Segmentation
    　　 3. Shota Harada, Ryoma Bise, Kengo Araki, Akihiko Yoshizawa, Kazuhiro Terada, Mariyo Kurata, Naoki Nakajima, Hiroyuki Abe, Tetsuo Ushiku, and Seiichi Uchida
    　　 Cluster-Guided Semi-Supervised Domain Adaptation for Imbalanced Medical Image Classification
    　　 4. Xiaoqing Liu, Kenji Ono, and Ryoma Bise
    　　 Mixing Data Augmentation with Preserving Foreground Regions in Medical Image Segmentation
    2022/10/11：Two papers have been accepted in WACV2023.
    　　 1. Takanori Asanomi, Kazuya Nishimura, and Ryoma Bise
    　　 Multi-Frame Attention with Feature-Level Warping for Drone Crowd Tracking
    　　 2. Kazuya Nishimura, and Ryoma Bise
    　　 Weakly Supervised Cell-Instance Segmentation with Two Types of Weak Labels by Single Instance Pasting
    2022/10/11：One paper has been accepted in Arthritis Research & Therapy(IF:5.606).
    　　 Kazuki Miyama, Ryoma Bise, Satoshi Ikemura, et al.
    　　 Deep learning-based automatic-bone-destruction-evaluation system using contextual information from other joints
    2022/6：One paper has been accepted to MICCAI2020 (Top Conference in Medical image analysis, acceptance rate:31%)
    　　 T Asanomi, K Nishimura, H Song, J Hayashida, H Sekiguchi, T Yagi, I Sato, and R Bise
    　　 Unsupervised Deep Robust Non-Rigid Alignment by Low-Rank Loss and Multi-Input Attention
    　　 International Conference on Medical Image Computing and Computer Assisted Intervention, 2022
    2022/4：One paper has been accepted in MedIA (IF:8.545)
    　　 Hyeonwoo Cho, Kazuya Nishimura, Kazuhide Watanabe, and Ryoma Bise
    　　 Effective pseudo-labeling based on heatmap for unsupervised domain adaptation in cell detection
    　　 Medical Image Analysis, 2022
    2022/1：One paper has been accepted in WACV2022
    　　 J Hayashida, K Nishimura, R Bise
    　　 Consistent Cell Tracking in Multi-Frames With Spatio-Temporal Context by Object-Level Warping Loss
    　　 IEEE/CVF Winter Conference on Applications of Computer Vision(WACV), 2022
    2021/5/14：4 papers are accepted to MICCAI2020 (Top Conference in Medical image analysis)
    　　 1. Hyeonwoo Cho, Kazuya Nishimura, Kazuhide Watanabe, and Ryoma Bise
    　　 Cell Detection in Domain Shift Problem Using Pseudo-Cell-Position Heatmapg
    　　 International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2021),
    　　 2. Kazuya Nishimura, Hyeonwoo Cho, and Ryoma Bise
    　　 Semi-supervised Cell Detection in Time-lapse Images Using Temporal Consistency
    　　 3. Kazuma Fujii, Daiki Suehiro, Kazuya Nishimura, and Ryoma Bise
    　　 Cell Detection from Imperfect Annotation by Pseudo Label Selection Using P-classification
    　　 4. Shota Harada, Ryoma Bise, Hideaki Hayashi, Kiyohito Tanaka and Seiichi Uchida
    　　 Order-Guided Disentangled Representation Learning for Ulcerative Colitis Classification with Limited Labels
    2021/5/12：One paper is accepted to MIA (Top Journal in Medical image analysis, IF:11.148)
    　　 Shota Harada, Ryoma Bise, Hideaki Hayashi, Kiyohito Tanaka, Seiichi Uchida
    　　 Soft and Self Constrained Clustering for Group-Based Labeling
    　　 Medical Image Analysis, 2021
    2020/7/3：Two papers are accepted in ECCV2020 (Top Conference in Computer Vision, acceptance rate:27%)。
    　　 1. K. Nishimura, J. Hayashida, C. Wang, D.F.E. Ker, and R. Bise
    　　 Weakly-Supervised Cell Tracking via Backward-and-Forward Propagation
    　　 2. H. Tokunaga, B.K. Iwana, Y. Teramoto, A. Yoshizawa, and R. Bise
    　　 Negative Pseudo Labeling using Class Proportion for Semantic Segmentation in Pathology
    2020/05/19：One paper is accepted to MICCAI2020 (Top Conference in Medical image analysis)
    　　 M. Shimano, Y. Asano, S. Ishihara, R. Bise, and I. Sato,
    　　 Imaging Scattering Characteristics of Tissue in Transmitted Microscopy
    2020/02/24:One paper is accepted in CVPR2020 (oral, Top Conference in Computer Vision, acceptance rate:22%)
    　　 J. Hayashida, K. Nishimura and R. Bise,
    　　 MPM: Joint Representation of Motion and Position Map for Cell Tracking pdf
    2020/06/30：Three papers are accepted to MICCAI2019 (Top Conference in Medical image analysis, acceptance rate: 31%)
    　　 R. Bise, K. Abe, H. Hayashi, K. Tanaka, and S. Uchida, Efficient Soft-Constrained Clustering for Group-Based Labeling
    　　 K. Nishimura, E.D. Ker, and R. Bise, Weakly Supervised Cell Segmentation in Dense by Propagating from Detection Map
    　　 J. Hayashida, and R. Bise, Cell Tracking with Deep Learning for Cell Detection and Motion Estimation in Low-Frame-Rate
    2020/06/20:One paper is accepted in CVPR2019 (Top Conference in Computer Vision, Poster, acceptance rate:25%)
    　　 H. Tokunaga, Y. Teramoto, A. Yoshizawa, R. Bise,
    　　 Adaptive Weighting Multi-Field-of-View CNN for Semantic Segmentation in Pathology

Publications

Awards

    in preparation

Curriculum Vitae

    2000.4 Graduate School of Information Science and Electrical Engineering, Kyushu University
    2002.3 Recived Master Degree from Kyushu University
    2002.4 Dai Nippon Printing （C&I IT Research Center）
    2008.7 Carnegie Mellon University, Robotics Institute（Visiting Scholor,supervisor:Prof. Takeo Kanade ）
    2011.1 Return to Japan, Dai Nippon Printing Research & Development Center, Team Reader
    2012.4 Graduate School of Interdisciplinary Information Studies, The University of Tokyo（supervisor:Prof. Yoichi Sato）
    2015.5 Recieved Ph.D.（Interdisciplinary Information Studies）
    2015.9 Leave Dai Nippon Printing
    2015.10 National Institute of Informatics, Associate Professor in special appointment（Sato Imari Lab.）
    2015.10 Breast Surgery, Faculty of Medicine Kyoto University, Visiting Scholor
    2017.3 Leave National Institute of Informatics
    2017.4 Faculty of Information Science and Electrical Engineering, Kyushu University, Associate Professor
    2017.4 National Institute of Informatics, Visiting Associate Professor
    2017.11 Department of Anatomy, School of Medicine, Keio University, Part-time Lecturer
    2023.12 Faculty of Information Science and Electrical Engineering, Kyushu University, Professor

E-mail

    E-mail: bise[at]ait.kyushu-u.ac.jp