Cell image analysis and generation

Selected Nature Comunications, 16, 9705, 2025.

Single-cell synaptome mapping of endogenous protein subpopulations in mammalian brain

Motokazu Uchigashima, Risa Iguchi, Kazuma Fujii, Kaito Shiku, Ryoma Bise, et. al.,

Chemical tags visualize proteins across synapses of an individual neuron.

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Selected Nature communications. 15, 1, 3657, 2024. (IF:17.7)

Precise immunofluorescence canceling for highly multiplexed imaging to capture specific cell states

Kosuke Tomimatsu, Takeru Fujii, Ryoma Bise, Kazufumi Hosoda, Yosuke Taniguchi, Hiroshi Ochiai, Hiroaki Ohishi, Kanta Ando, Ryoma Minami, Kaori Tanaka, Taro Tachibana, Seiichi Mori, Akihito Harada, Kazumitsu Maehara, Masao Nagasaki, Seiichi Uchida, Hiroshi Kimura, Masashi Narita, and Yasuyuki Ohkawa

Sequential fluorescence removal enables repeated staining of the same cells.

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Selected International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2023), 2023,(top

Mitosis Detection from Partial Annotation by Dataset Generation via Frame-Order Flipping

Kazuya Nishimura, Ami Katanaya, Shinichiro Chuma, and Ryoma Bise

Reversing cell image sequences helps detect mitosis from limited annotations.

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Selected International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2021), 2021, (ac

Semi-supervised Cell Detection in Time-lapse Images Using Temporal Consistency

Kazuya Nishimura, Hyeonwoo Cho, and Ryoma Bise

Temporal consistency between microscopy frames supports detection with few labels.

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Selected International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2021), 2021, (ac

Cell Detection from Imperfect Annotation by Pseudo Label Selection Using P-classification

Kazuma Fujii, Daiki Suehiro, Kazuya Nishimura, and Ryoma Bise

Unannotated cells are selected as pseudo-labels to train a detector.

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Selected IEEE CVPR, 2020. (oral, Top Conference in Computer Vision, acceptance rate:22%) [pdf]

MPM: Joint Representation of Motion and Position Map for Cell Tracking

J. Hayashida, K. Nishimura and R. Bise

One map jointly represents cell positions and motion between frames.

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Selected International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2019), 2019, (to

Weakly Supervised Cell Segmentation in Dense by Propagating from Detection Map

K. Nishimura, E.D. Ker, and R. Bise

Weak cell-position labels guide instance segmentation in dense images.

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Selected International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2019), 2019,(top

Cell Tracking with Deep Learning for Cell Detection and Motion Estimation in Low-Frame-Rate

J. Hayashida, and R. Bise

Cell detection and motion estimation are combined to track cells in low frame rate images.

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1. Rethinking Microscopy Generation: Co-Designed Diffusion for Biologically Interpretable Single-Cell Synthesis
   Shumpei Takezaki, Duway Nicolas Lesmes-Leon, Ryoma Bise, Gillian Lovell, Bianca Migliori, Andreas Dengel, and Sheraz Ahmed · British Machine Vision Conference (BMVC), 2026.
2. Cell Instance Segmentation via Multi-Task Image-to-Image Schrödinger Bridge
   Hayato Inoue, Shota Harada, Shumpei Takezaki, and Ryoma Bise · International Joint Conference on Neural Networks (IJCNN), 2026.
3. Bridging the Density Gap: Diffusion Model for Stepwise Generation of Dense Cell Images from Sparse Data
   Masashi Tahara, Kazuya Nishimura, Shumpei Takezaki, and Ryoma Bise · IEEE 23rd International Symposium on Biomedical Imaging (ISBI), 2026. (Best Paper Runners-Up Award)
4. Single-cell synaptome mapping of endogenous protein subpopulations in mammalian brain
   Motokazu Uchigashima, Risa Iguchi, Kazuma Fujii, Kaito Shiku, Ryoma Bise, et. al., · Nature Comunications, 16, 9705, 2025.
5. NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models.
   Shumpei Takezaki, Ryoma Bise, Shinnosuke Matsuo · International Conference on Computer Vision Workshop LIMIT (ICCVW), 2025.
6. Label-free live cell recognition and tracking for biological discoveries and translational applications
   Biqi Chen, Zi Yin, Billy Wai-Lung Ng, Dan Michelle Wang, Rocky S Tuan, Ryoma Bise, and Dai Fei Elmer Ker · npj Imaging, 2, 41, 2024.
7. Precise immunofluorescence canceling for highly multiplexed imaging to capture specific cell states
   Kosuke Tomimatsu, Takeru Fujii, Ryoma Bise, Kazufumi Hosoda, Yosuke Taniguchi, Hiroshi Ochiai, Hiroaki Ohishi, Kanta Ando, Ryoma Minami, Kaori Tanaka, Taro Tachibana, Seiichi Mori, Akihito Harada, Kazumitsu Maehara, Masao Nagasaki, Seiichi Uchida, Hiroshi Kimura, Masashi Narita, and Yasuyuki Ohkawa · Nature communications. 15, 1, 3657, 2024. (IF:17.7)
8. Analysis of optical absorption of photoaged human skin using a high-frequency illumination microscopy analysis system
   Yuki Ogura, Mihoko Shimano, Ryoma Bise, Toyonobu Yamashita, Chika Katagiri, and Imari Sato · Experimental Dermatology, 32, 9, pp.1402-1411, 2023. (IF:3.6)
9. Mitosis Detection from Partial Annotation by Dataset Generation via Frame-Order Flipping
   Kazuya Nishimura, Ami Katanaya, Shinichiro Chuma, and Ryoma Bise · International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2023), 2023,(top conference in medial image analysis)
10. Cell Tracking in C. elegans with Cell Position Heatmap-Based Alignment and Pairwise Detection
    Kaito Shiku, Hiromitsu Shirai, Takeshi Ishihara, and Ryoma Bise · International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC),2023
11. Multi-Frame Attention with Feature-Level Warping for Drone Crowd Tracking
    Takanori Asanomi, Kazuya Nishimura, and Ryoma Bise · Winter Conference on Applications of Computer Vision 2023 (WACV2023),2023. (accepted)
12. Weakly Supervised Cell-Instance Segmentation with Two Types of Weak Labels by Single Instance Pasting
    Kazuya Nishimura, and Ryoma Bise · Winter Conference on Applications of Computer Vision 2023 (WACV2023),2023. (accepted)
13. Multi-Class Cell Detection Using Modified Self-Attention
    T Sugimoto, H Ito, Y Teramoto, A Yoshizawa and R Bise · CVPR Workshop, Computer Vision for Microscopy Image Analysis (CVMI), 2022
14. Consistent Cell Tracking in Multi-Frames With Spatio-Temporal Context by Object-Level Warping Loss
    J Hayashida, K Nishimura, R Bise · IEEE/CVF Winter Conference on Applications of Computer Vision, pp.1727-1736, 2022
15. Weakly Supervised Cell Instance Segmentation Under Various Conditions
    K Nishimura, C Wang, K Watanabe, R Bise · Medical Image Analysis, vol.73, 102182, https://doi.org/10.1016/j.media.2021.102182, 2021, October (top journal in medicalImage analysis, IF:11.148)
16. Semi-supervised Cell Detection in Time-lapse Images Using Temporal Consistency
    Kazuya Nishimura, Hyeonwoo Cho, and Ryoma Bise · International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2021), 2021, (accepted, top conference in medial image analysis)
17. Cell Detection from Imperfect Annotation by Pseudo Label Selection Using P-classification
    Kazuma Fujii, Daiki Suehiro, Kazuya Nishimura, and Ryoma Bise · International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2021), 2021, (accepted, top conference in medial image analysis)
18. Light‐sheet microscopy‐based 3D single‐cell tracking reveals a correlation between cell cycle and the start of endoderm cell internalization in early zebrafish development
    Akiko Kondow, Kiyoshi Ohnuma, Yasuhiro Kamei, Atsushi Taniguchi, Ryoma Bise, Yoichi Sato, Hisateru Yamaguchi, Shigenori Nonaka, and Keiichiro Hashimoto · Development, Growth and Differentiation, vol.62(7), pp.495--502, https://doi.org/10.1111/dgd.12695, 2020, November, (IF:1.723)
19. Weakly-Supervised Cell Tracking via Backward-and-Forward Propagation
    K. Nishimura, J. Hayashida, C. Wang, D.F.E. Ker, and R. Bise · 16th European Conference on Computer Vision (ECCV2020) 2020, (accepted, Top Conference in Computer Vision, acceptance rate:27%)
20. Imaging Scattering Characteristics of Tissue in Transmitted Microscopy
    M. Shimano, Y. Asano, S. Ishihara, R. Bise, and I. Sato · International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2020), 2020, (accepted, top conference in medial image analysis)
21. Spatial-Temporal Mitosis Detection in Phase-Contrast Microscopy Via Likelihood Map Estimation by 3DCNN
    K. Nishimura and R. Bise · Proceedings of 42st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2020. [pdf]
22. MPM: Joint Representation of Motion and Position Map for Cell Tracking
    J. Hayashida, K. Nishimura and R. Bise · IEEE CVPR, 2020. (oral, Top Conference in Computer Vision, acceptance rate:22%) [pdf]
23. Weakly Supervised Cell Segmentation in Dense by Propagating from Detection Map
    K. Nishimura, E.D. Ker, and R. Bise · International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2019), 2019, (top conference in medial image analysis, early acceptance rate:16%)
24. Cell Tracking with Deep Learning for Cell Detection and Motion Estimation in Low-Frame-Rate
    J. Hayashida, and R. Bise · International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2019), 2019,(top conference in medial image analysis, early acceptance rate:16%)
25. Phase Contrast Time-Lapse Microscopy Datasets with Automated and Manual Cell Tracking Annotations
    E. Ker, S. Eom, S. Sanami, R. Bise, et. al. · Scientific Data, doi: 10.1038/sdata.2018.237, 2019. (IF:5.305)
26. Separation of Transmitted Light and Scattering Components in Transmitted Microscopy
    M. Shimano, R. Bise, Y. Zheng, and I. Sato · International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2016), pp.702-710, 2017,(top conference in medial image analysis, acceptance rate:33%)
27. Cell Detection Method from Redundant Candidates under the Non-Overlapping Constraints
    R. Bise and Y. Sato · IEEE Trans. on Medical Imaging, 34(7), pp.1417-1427, 2015. (IF:3.799)
28. Cell Tracking Under High Confluency Conditions by Candidate Cell Region Detection Based Association Approach
    R. Bise, Y. Maeda, M.H. Kim, and M. Kino-oka · Proceedings of BioMed 2013(oral)
29. Mechanical characterization of adult stem cells from bone marrow and perivascular niches
    AJS. Ribeiro, S. Tottey, RWE. Taylor, R. Bise, T. Kanade, SF. Badylak, and KN. Dahl, · Journal of biomechanics, 45(7), pp.1280-1287, 2012. (IF:2.496)
30. Automated Mitosis Detection of Stem Cell Populations in Phase-Contrast Microscopy Images
    S. Huh, E. Ker, R. Bise, M. Chen, and T. Kanade · IEEE Trans. Med. Imaging, 30(3),pp.586-596, 2011 (IF:3.799)
31. Automatic Cell Tracking Applied to Analysis of Cell Migration in Wound Healing Assay
    R. Bise, T. Kanade, Z. Yin, and S. Huh · Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp.6174-6179, 2011(oral)
32. Reliable Cell Tracking by Global Data Association Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI)
    R. Bise, Z. Yin, and T. Kanade · pp.1004-1010, 2011.(oral,acceptance rate < 18%)
33. Mitosis Detection for Stem Cell Tracking in Phase-Contrast Microscopy Images Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI)
    S. Huh, S. Eom, R. Bise, Z. Yin, and T. Kanade · pages 2121-2127, 2011
34. Cell Image Analysis: Algorithms, System and Applications Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV)
    T. Kanade, Z. Yin, R. Bise, S. Huh, S. Eom, M. Sandbothe and M. Chen · pp.374-381, 2011
35. Detection of Hematopoietic Stem Cells in Microscopy Images Using a Bank of Ring Filters Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI)
    S. Eom, R. Bise, and T. Kanade · pp.137-140, 2010
36. Cell Segmentation in Microscopy Imagery Using a Bag of Local Bayesian Classifiers Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI)
    Z. Yin, R. Bise, M. Chen, and T. Kanade · pp.125-128, 2010
37. Reliably Tracking Partially Overlapping Neural Stem Cells in DIC Microscopy Image Sequences Proceedings of MICCAI Workshop on OPTMHisE
    R. Bise, K. Li, S. Eom, and T. Kanade · pp.67-77, 2009
38. An engineered approach to stem cell culture: automating the decision process for real-time adaptive subculture of stem cells
    D.F.E. Ker, L.E Weiss, S.N Junkers, M. Chen, Z. Yin, M.F. Sandbothe, S. Huh, S. Eom, R. Bise, E. Osuna-Highley, T. Kanade, and P.G Campbell · PloS one 6 (11), e27672. (IF:3.534)
39. BTracking of hematopoietic stem cells in microscopy images for lineage determination
    S. Eom, S. Huh, D. F. E. Ker, R. Bise, and T. Kanade · IEEE Trans. Biomedical engineering, (accepted,IF:2.233)

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