A paper was accepted at NeurIPS 2026.
Kaito Shiku, Kazuya Nishimura, Yasuhiro Kojima, and Ryoma Bise
Preserving DEG Rankings for Gene Discovery in Histology-Based Spatial Gene Expression Prediction

Ryoma Bise Professor · Ph.D. (Interdisciplinary Information Studies)
Human Interface Laboratory
Department of Advanced Information Technology
Faculty of Information Science and Electrical Engineering · Kyushu University
Kyushu University Center for Mathematics and Data Science Education · Division Head
National Institute of Informatics · Visiting Associate Professor
I study biomedical image analysis and learning from limited labels, connecting microscopy, pathology, vascular imaging, and spatial transcriptomics.
A paper was accepted at NeurIPS 2026.
Kaito Shiku, Kazuya Nishimura, Yasuhiro Kojima, and Ryoma Bise
Preserving DEG Rankings for Gene Discovery in Histology-Based Spatial Gene Expression Prediction
A paper was accepted at BMVC 2026 (acceptance rate: 404/1,448 = 27.9%).
Shumpei Takezaki, Duway Nicolas Lesmes-Leon, Ryoma Bise, Gillian Lovell, Bianca Migliori, Andreas Dengel, and Sheraz Ahmed
Rethinking Microscopy Generation: Co-Designed Diffusion for Biologically Interpretable Single-Cell Synthesis
A paper was selected for a Spotlight Oral presentation at ICIP 2026 (top 8% of accepted papers).
Phuong Ngoc Nguyen, Kaito Shiku, Ryoma Bise, Seiichi Uchida, and Shinnosuke Matsuo
Leveraging Vision-Language Models as Weak Annotators in Active Learning
A paper was published in ICASSP 2026.
Kohki Akiba, Shinnosuke Matsuo, Shota Harada, and Ryoma Bise
Leveraging Label Proportion Prior for Class-Imbalanced Semi-Supervised Learning
The following paper received the Best Paper Runners-Up Award at IEEE ISBI 2026 (top three among 1,750 papers).
M. Tahara, K. Nishimura, S. Takezaki, and R. Bise
One paper has been accepted in CVPR 2026 (CVPR2026) (Top conference in Computer Vision, acceptance rate:4,090/16,092=25.42%)
Kazuya Nishimura, Ryoma Bise, Shinnosuke Matsuo, Haruka Hirose, and Yasuhiro Kojima
Cell-Type Prototype-Informed Neural Network for Gene Expression Estimation from Pathology Images
Four papers have been accepted in ISBI2026
One paper has been accepted in AAAI 2026 (AAAI2026) (Top conference in AI, acceptance rate:4,167/23,680=17.6%)
Kaito Shiku, Kazuya Nishimura, Shinnosuke Matsuo, Yasuhiro Kojima, and Ryoma Bise
Auxiliary Gene Learning: Spatial Gene Expression Estimation by Auxiliary Gene Selection
Soichi Mita received the FY2025 IEICE PRMU Research Encouragement Award.
PRMU2025-36, “Vessel Centerline Estimation from 3D CT Images Using Diffusion Models”
Kaito Shiku received the 25th IEEE Fukuoka Section Student Research Encouragement Award.
Ordinal Multiple-instance Learning for Ulcerative Colitis Severity Estimation with Selective Aggregated Transformer (WACV 2025, pp. 4290–4299)
Mikio Osajima received the Presentation Encouragement Award at the 78th Joint Conference of Electrical, Electronics and Information Engineers in Kyushu.
“Adaptive Selection of Medical Tests”
Soichi Mita received the IPSJ Kyushu Branch Encouragement Award at the 78th Joint Conference of Electrical, Electronics and Information Engineers in Kyushu.
“Vessel Extraction from CT Images Using a Generative Model”
One paper has been accepted in NeurIPS 2025 (NeurIPS2025) (Top conference in machine learning, acceptance rate:24%)
Learning to Relative Expression under Batch Effects and Stochastic Noise in Spatial Transcriptomics
One paper has been accepted in MICCAI2025 (Top conference in medical image analysis, acceptance rate:29%)
Junda Liao, Chu Zhou, Yuta Asano, Yushi Suzuki, Ryoma Bise, Nobuaki Imanishi, Kazuo Kishi, Sadakazu Aiso, and Imari Sato
Vascular Photoacoustic Volume Registration via 2D Feature Matching with Reverse Mapping Based on Maximum Intensity Projection
One paper has been accepted in CVPR2025 (Top conference in computer vision, acceptance rate:22.1%)
Shinnosuke Matsuo, Riku Togashi, Ryoma Bise, Seiichi Uchida, and Masahiro Nomura
Instance-wise Supervision-level Optimization in Active Learning
One paper has been accepted in WACV2025 (Core Rank A, acceptance rate in Round 1:12% (167/1381))
Kaito Shiku, Kazuya Nishimura, Daiki Suehiro, Kiyohito Tanaka, and Ryoma Bise
Ordinal Multiple-instance Learning for Ulcerative Colitis Severity Estimation with Selective Aggregated Transformer
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
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
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
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
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
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
I am promoted to a Professor.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
Ongoing projects
Additional individual collaborations with academic and external partners.
2026: Coauthor of “Bridging the Density GAP: Diffusion Model for Stepwise Generation of Dense Cell Images from Sparse Data,” recipient of the Best Paper Runners-Up Award at IEEE ISBI 2026 (top three among 1,750 papers).
| 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 | |
| 2017.11–2022 | Department of Anatomy, School of Medicine, Keio University, Part-time Lecturer | |
| 2023.12 | Faculty of Information Science and Electrical Engineering, Kyushu University, Professor |