Publication List（Ryoma Bise）


Google Scholar（Ryoma Bise）



Peer Reviwed Papers
  1. Takumi Okuo, Shinnosuke Matsuo, Shota Harada, Kiyohito Tanaka, and Ryoma Bise
    Weakly-Supervised Domain Adaptation with Proportion-Constrained Pseudo-Labeling
    International Joint Conference on Neural Networks (IJCNN), 2025
  2. Masashi Tahara, and Ryoma Bise
    Medical Image Alignment for Different Resolutions and Fields of View Using Contrastive Learning with Feature-Level Similarity
    International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC),2025
  3. Shinnosuke Matsuo, Riku Togashi, Ryoma Bise, Seiichi Uchida, and Masahiro Nomura
    Instance-wise Supervision-level Optimization in Active Learning
    IEEE CVPR, 2025. (Top Conference in Computer Vision, acceptance rate:22.1%)
  4. Kazuya Nishimura, Ryoma Bise, and Yasuhiro Kojima
    Towards Spatial Transcriptomics-Guided Pathological Image Recognition With Batch-Agnostic Encoder
    IEEE International Symposium on Biomedical Imaging (ISBI), 2025.
  5. Kaito Shiku, Kazuya Nishimura, Daiki Suehiro, Kiyohito Tanaka, and Ryoma Bise
    Ordinal Multiple-instance Learning for Ulcerative Colitis Severity Estimation with Selective Aggregated Transformer
    IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025. (accepted, acceptance rate in Round 1:12% (167/1381) )
  6. Tatsuhiro Eguchi, Shumpei Takezaki, Mihoko Shimano, Takayuki Yagi, and Ryoma Bise
    Guidance-base Diffusion Models for Improving Photoacoustic Image Quality
    The British Machine Vision Conference (BMVC), 2024. (accepted, acceptance rate:25.8% (264/1020) )
  7. 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
    European Conference on Artificial Intelligence (ECAI), 2024. (acceptted, acceptance rate:23% (547/2344) )
  8. Takehiro Yamane, Itaru Tsuge, Susumu Saito, and Ryoma Bise
    Adaptive Pseudo Label Selection for Individual Unlabeled Data by Positive and Unlabeled Learning
    MICCAI Workshop (ADSMI), 2024. (acceptted)
  9. 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
    Medical Image Analysis, 2024. (accepted, IF:10.7)
  10. Shinnosuke Matsuo, Daiki Suehiro, Seiichi Uchida, Hiroaki Ito, Kazuhiro Terada, Akihiko Yoshizawa and Ryoma Bise
    Learning from Partial Label Proportions for Whole Slide Image Segmentation
    International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI),2024. (Early Accept, acceptance rate:11%)
  11. Yuki Shigeyasu, Shota Harada, Akihiko Yoshizawa, Kazuhiro Terada, and Ryoma Bisee
    Diameter-based pseudo labeling for pathological image segmentation
    International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC),2024
  12. Yuki Shigeyasu, Shota Harada, Akihiko Yoshizawa, Kazuhiro Terada, Naoki Nakazima, Mariyo Kurata, Hiroyuki Abe, Tetsuo Ushiku, and Ryoma Bise
    Domain Generalization for Pathological Images Using the Storage Period Information
    IEEE International Symposium on Biomedical Imaging (ISBI), 2024.
  13. Hiroaki Ito, Akihiko Yoshizawa, Kazuhiro Terada, Akiyoshi Nakakura, Mariyo Rokutan-Kurata, Tatsuhiko Sugimoto, Kazuya Nishimura, Naoki Nakajima, Shinji Sumiyoshi, Masatsugu Hamaji, Toshi Menju, Hiroshi Date, Satoshi Morita, Ryoma Bise, Hironori Haga
    A Deep Learning?Based Assay for Programmed Death Ligand 1 Immunohistochemistry Scoring in Non?Small Cell Lung Carcinoma: Does it Help Pathologists Score?
    Modern Pathology. 37, 6, 100485, 2024. (IF:8.209)
  14. Xiaoqing Liu, KenjiOno, and Ryoma Bise
    A data augmentation approach that ensures the reliability of foregrounds in medical image segmentation
    Image and Vision Computing, 147, 105056, 2024. (IF:4.2)
  15. Kazuki Miyama, Takenori Akiyama, Ryoma Bise, Shunsuke Nakamura, Yasuharu Nakashima, and Seiichi Uchida
    Development of an automatic surgical planning system for high tibial osteotomy using artificial intelligence
    Knee. 48, pp.128-137, 2024. (IF:1.9)
  16. 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
    Precise immunofluorescence canceling for highly multiplexed imaging to capture specific cell states
    Nature communications. 15, 1, 3657, 2024. (IF:17.7)
  17. 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,(Top Conference in Signal Processing)
  18. Kengo Kawaguchi, Kazuki Miyama, Makoto Endo, Ryoma Bise, Kenichi Kohashi, Takeshi Hirose, Akira Nabeshima, Toshifumi Fujiwara, Yoshihiro Matsumoto, Yoshinao Oda, and Yasuharu Nakashima
    Viable tumor cell density after neoadjuvant chemotherapy assessed using deep learning model reflects the prognosis of osteosarcoma
    npj　Precision Oncology, 2024 (Top Journal on Oncology, IF:10.123)
  19. Kazuhiro Terada, Akihiko Yoshizawa, Xiaoqing Liu, Hiroaki Ito, Masatsugu Hamaji, Toshi Menju, Hiroshi Date, Ryoma Bise, and Hironori Haga
    Deep Learning for Predicting Effect of Neoadjuvant Therapies in Non?small Cell Lung Carcinomas With Histologic Images
    Modern Pathology, 2024 (Top Journal on Pathology, IF:8.209)
  20. Yuki Ogura, Mihoko Shimano, Ryoma Bise, Toyonobu Yamashita, Chika Katagiri, and Imari Sato
    Analysis of optical absorption of photoaged human skin using a high-frequency illumination microscopy analysis system
    Experimental Dermatology, 32, 9, pp.1402-1411, 2023. (IF:3.6)
  21. Kaoru Takabayashi, Taku Kobayashi, Katsuyoshi Matsuoka, Barrett G Levesque, Takuji Kawamura, Kiyohito Tanaka, Takeaki Kadota, Ryoma Bise, Seiichi Uchida, Takanori Kanai, and Haruhiko Ogata
    Artificial intelligence quantifying endoscopic severity of ulcerative colitis in gradation scale
    Digestive Endoscopy, 32, 9, pp.1402-1411, 2023 (IF:6.337)
  22. 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,(top conference in computer vision)
  23. Takumi Okuo, Kazuya Nishimura, Hiroaki Ito, Kazuhiro Terada, Akihiko Yoshizawa, and Ryoma Bise
    Proportion Estimation by Masked Learning from Label Proportion
    Workshop on MICCAI: DALI, pp.117-126, 2023.
  24. Kazuya Nishimura, Ami Katanaya, Shinichiro Chuma, and Ryoma Bise
    Mitosis Detection from Partial Annotation by Dataset Generation via Frame-Order Flipping
    International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2023),
    2023,(top conference in medial image analysis)
  25. Kaito Shiku, Hiromitsu Shirai, Takeshi Ishihara, and Ryoma Bise
    Cell Tracking in C. elegans with Cell Position Heatmap-Based Alignment and Pairwise Detection
    International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC),2023
  26. Shinnosuke Matsuo, Ryoma Bise, Seiichi Uchida, and Daiki Suehiro
    Learning From Label Proportion with Online Pseudo-Label Decision by Regret Minimization
    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP2023),2023
    (top conference in signal processing)
  27. Yuki Shigeyasu, Shota Harada, Kengo Araki, Akihiko Yoshizawa, Kazuhiro Terada, and Ryoma Bise
    Spatial Distribution-based Pseudo Labeling for Pathological Image Segmentation
    IEEE International Symposium on Biomedical Imaging (ISBI), 2023.
  28. 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
    IEEE International Symposium on Biomedical Imaging (ISBI), 2023. (Oral)
  29. 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
    IEEE International Symposium on Biomedical Imaging (ISBI), 2023.
  30. Xiaoqing Liu, Kenji Ono, and Ryoma Bise
    Mixing Data Augmentation with Preserving Foreground Regions in Medical Image Segmentation
    IEEE International Symposium on Biomedical Imaging (ISBI), 2023. (Oral)
  31. Takanori Asanomi, Kazuya Nishimura, and Ryoma Bise
    Multi-Frame Attention with Feature-Level Warping for Drone Crowd Tracking
    Winter Conference on Applications of Computer Vision 2023 (WACV2023),2023. (accepted)
  32. Kazuya Nishimura, and Ryoma Bise
    Weakly Supervised Cell-Instance Segmentation with Two Types of Weak Labels by Single Instance Pasting
    Winter Conference on Applications of Computer Vision 2023 (WACV2023),2023. (accepted)
  33. Kazuki Miyama, Ryoma Bise, Satoshi Ikemura, Kazuhiro Kai, Masaya Kanahori, Shinkichi Arisumi, Taisuke Uchida, Yasuharu Nakashima, and Seiichi Uchida
    Deep learning-based automatic-bone-destruction-evaluation system using contextual information from other joints
    Arthritis Research & Therapy, 2022. (IF:5.606)
  34. 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 (MICCAI2022),
    2022,(top conference in medial image analysis)
  35. T Sugimoto, H Ito, Y Teramoto, A Yoshizawa and R Bise
    Multi-Class Cell Detection Using Modified Self-Attention
    CVPR Workshop, Computer Vision for Microscopy Image Analysis (CVMI), 2022
  36. 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, vol.79, 102436, https://doi.org/10.1016/j.media.2022.102436, 2022
    (top journal in medicalImage analysis, IF:13.828)
  37. 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, pp.1727-1736, 2022
  38. K Nishimura, C Wang, K Watanabe, R Bise
    Weakly Supervised Cell Instance Segmentation Under Various Conditions
    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)
  39. K Araki, M Rokutan-Kurata, K Terada, A Yoshizawa, R Bise
    Patch-Based Cervical Cancer Segmentation using Distance from Boundary of Tissue
    International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021
  40. R Kikkawa, H Kajita, N Imanishi, S Aiso, R Bise
    Unsupervised Body Hair Detection by Positive-Unlabeled Learning in Photoacoustic Image
    International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021
  41. Kazuya Nishimura, Hyeonwoo Cho, and Ryoma Bise
    Semi-supervised Cell Detection in Time-lapse Images Using Temporal Consistency
    International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2021),
    2021, (accepted, top conference in medial image analysis)
  42. Kazuma Fujii, Daiki Suehiro, Kazuya Nishimura, and Ryoma Bise
    Cell Detection from Imperfect Annotation by Pseudo Label Selection Using P-classification
    International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2021),
    2021, (accepted, top conference in medial image analysis)
  43. Shota Harada, Ryoma Bise, Hideaki Hayashi, Kiyohito Tanaka and Seiichi Uchida
    Order-Guided Disentangled Representation Learning for Ulcerative Colitis Classification with Limited Labels
    International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2021),
    2021, (accepted, top conference in medial image analysis)
  44. Hyeonwoo Cho, Kazuya Nishimura, Kazuhide Watanabe, and Ryoma Bise
    Cell Detection in Domain Shift Problem Using Pseudo-Cell-Position Heatmap
    International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2021),
    2021, (accepted, top conference in medial image analysis, Provisional acceptance rate:13%)
  45. Shota Harada, Ryoma Bise, Hideaki Hayashi, Kiyohito Tanaka, and Seiichi Uchida
    Soft and Self Constrained Clustering for Group-Based Labeling
    Medical Image Analysis, https://doi.org/10.1016/j.media.2021.102097, 2021, May
    (in press, top journal in medicalImage analysis, IF:11.148)
  46. Akiko Kondow, Kiyoshi Ohnuma, Yasuhiro Kamei, Atsushi Taniguchi, Ryoma Bise, Yoichi Sato, Hisateru Yamaguchi, Shigenori Nonaka, and Keiichiro Hashimoto
    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
    Development, Growth and Differentiation, vol.62(7), pp.495--502, https://doi.org/10.1111/dgd.12695, 2020, November, (IF:1.723)
  47. K. Nishimura, J. Hayashida, C. Wang, D.F.E. Ker, and R. Bise
    Weakly-Supervised Cell Tracking via Backward-and-Forward Propagation
    16th European Conference on Computer Vision (ECCV2020)
    2020, (accepted, Top Conference in Computer Vision, acceptance rate:27%)
  48. H. Tokunaga, B.K. Iwana, Y. Teramoto, A. Yoshizawa, and R. Bise
    Negative Pseudo Labeling using Class Proportion for Semantic Segmentation in Pathology
    16th European Conference on Computer Vision (ECCV2020)
    2020, (accepted, Top Conference in Computer Vision, acceptance rate:27%)
  49. M. Shimano, Y. Asano, S. Ishihara, R. Bise, and I. Sato
    Imaging Scattering Characteristics of Tissue in Transmitted Microscopy
    International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2020),
    2020, (accepted, top conference in medial image analysis)
  50. K. Nishimura and R. Bise
    Spatial-Temporal Mitosis Detection in Phase-Contrast Microscopy Via Likelihood Map Estimation by 3DCNN
    Proceedings of 42st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2020.
    [pdf]
  51. J. Hayashida, K. Nishimura and R. Bise
    MPM: Joint Representation of Motion and Position Map for Cell Tracking
    IEEE CVPR, 2020. (oral, Top Conference in Computer Vision, acceptance rate:22%)
    [pdf]
  52. R. Bise, K. Abe, H. Hayashi, K. Tanaka, and S. Uchida
    Efficient Soft-Constrained Clustering for Group-Based Labeling
    International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2019),
    2019, (top conference in medial image analysis, acceptance rate:31%)
  53. K. Nishimura, E.D. Ker, and R. Bise
    Weakly Supervised Cell Segmentation in Dense by Propagating from Detection Map
    International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2019),
    2019, (top conference in medial image analysis, early acceptance rate:16%)
  54. J. Hayashida, and R. Bise
    Cell Tracking with Deep Learning for Cell Detection and Motion Estimation in Low-Frame-Rate
    International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2019),
    2019,(top conference in medial image analysis, early acceptance rate:16%)
  55. S. Harada, H. Hayashi, R. Bise, K. Tanaka, Q. Meng, and S. Uchida
    Endoscopic Image Clustering with Temporal Ordering Information Based on Dynamic Programming
    Proceedings of 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019.
  56. D. Harada, R. Bise, H. Tokunaga, W. Ohyama, S. Oka, T. Fujimori, and S. Uchida
    Scribbles for Metric Learning
    Proceedings of 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019.
  57. H. Tokunaga, Y. Teramoto, A. Yoshizawa, R. Bise
    Adaptive Weighting Multi-Field-of-View CNN for Semantic Segmentation in Pathology
    IEEE CVPR, 2019. (Top Conference in Computer Vision, Poster, acceptance rate:25%)
    pdf
  58. R. Kikkawa, H. Sekiguchi, I. Tsuge, S. Saito and R. Bise
    SEMI-SUPERVISED LEARNING WITH STRUCTURED KNOWLEDGE FOR BODY HAIR DETECTION IN PHOTOACOUSTIC IMAGE
    IEEE International Symposium on Biomedical Imaging (ISBI), 2019. (Oral)
  59. H Okawa, M Shimano, Y Asano, R Bise, K Nishino, I Sato
    Estimation of Wetness and Color From A Single Multispectral Image
    IEEE transactions on pattern analysis and machine intelligence, 10.1109/TPAMI.2019.2903496, 2019. (IF:9.455)
  60. S. Saito, R. Bise, et. al.
    Digital artery deformation on movement of the proximal interphalangeal joint
    Journal of Hand Surgery(European Volume), doi:1753193418807833, 2019. (IF:2.648)
  61. E. Ker, S. Eom, S. Sanami, R. Bise, et. al.
    Phase Contrast Time-Lapse Microscopy Datasets with Automated and Manual Cell Tracking Annotations
    Scientific Data, doi: 10.1038/sdata.2018.237, 2019. (IF:5.305)
  62. K. Kajiya, R. Bise, et. al.
    Light-sheet microscopy reveals site-specific 3-dimensional patterns of the cutaneous vasculature and pronounced rarefication in aged skin
    Journal of Dermatological Science, 92(1), pp.3-5, 2018. (IF: 3.675)
  63. Q. Chen, R. Bise, L. Gu, Y. Zheng, I. Sato, J.N. Hwang, N. Imanishi, and S. Aiso
    Virtual Blood Vessels in Complex Background using Stereo X-ray Images
    ICCV Workshop, BioImage Computing, 2017
  64. L. Gu, Y. Zheng, R. Bise, I. Sato, N. Imanishi, and S. Aiso
    Semi-Supervised Learning for Biomedical Image Segmentation via Forest Oriented Super Pixels(Voxels)
    International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI),
    pp.702-710, 2017,(top conference in medial image analysis, acceptance rate:33%)
  65. M. Shimano, R. Bise, Y. Zheng, and I. Sato
    Separation of Transmitted Light and Scattering Components in Transmitted Microscopy
    International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2016),
    pp.702-710, 2017,(top conference in medial image analysis, acceptance rate:33%)
  66. M. Shimano, H. Okawa, Y. Asano, R. Bise, K. Nishino, and I. Sato,
    Wetness and Color from a Single Multispectral Image
    IEEE Conference on Computer Vision and Pattern Recognition(CVPR),
    pp.3967-3975, 2017，(top conference in computer vision，oral, acceptance rate: 2.5%)．
  67. R. Bise, Y. Zheng, I. Sato, and M. Toi
    Vascular registration in Photoacoustic imaging by low-rank alignment via forground, background, and complement decomposition
    International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2016),
    pp.362-334,2016, (top conference in medial image analysis, early acceptance < 11%)
  68. R. Bise, I. Sato, K. Kajiya, and T. Yamashita
    3D structure modeling of dense capillaries by multi-objects tracking
    Proceedings of IEEE CVPR2016 Workshop: Computer Vision for Microscopy Analysis(CVMIA)
    pp.265-270, July. 2016
  69. N. Yasuda, H. Sekine, R. Bise, T. Okano, and T. Shimizu
    Tracing behavior of endothelial cells promotes vascular network formation
    Microvascular Research
    105, pp.125-131, 2016. (Impact Factor(IF):2.300)
  70. R. Bise and Y. Sato
    Cell Detection Method from Redundant Candidates under the Non-Overlapping Constraints
    IEEE Trans. on Medical Imaging, 34(7), pp.1417-1427, 2015. (IF:3.799)
  71. R. Bise, Y. Maeda, M.H. Kim, and M. Kino-oka
    Cell Tracking Under High Confluency Conditions by Candidate Cell Region Detection Based Association Approach
    Proceedings of BioMed 2013(oral)
  72. S. Huh, E. Ker, R. Bise, M. Chen, and T. Kanade
    Automated Mitosis Detection of Stem Cell Populations in Phase-Contrast Microscopy Images
    IEEE Trans. Med. Imaging, 30(3),pp.586-596, 2011 (IF:3.799)
  73. 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
    An engineered approach to stem cell culture: automating the decision process for real-time adaptive subculture of stem cells
    PloS one 6 (11), e27672. (IF:3.534)
  74. AJS. Ribeiro, S. Tottey, RWE. Taylor, R. Bise, T. Kanade, SF. Badylak, and KN. Dahl,
    Mechanical characterization of adult stem cells from bone marrow and perivascular niches
    Journal of biomechanics, 45(7), pp.1280-1287, 2012. (IF:2.496)
  75. S. Eom, S. Huh, D. F. E. Ker, R. Bise, and T. Kanade
    BTracking of hematopoietic stem cells in microscopy images for lineage determination
    IEEE Trans. Biomedical engineering, (accepted,IF:2.233)
  76. R. Bise, T. Kanade, Z. Yin, and S. Huh
    Automatic Cell Tracking Applied to Analysis of Cell Migration in Wound Healing Assay Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp.6174-6179, 2011(oral)
  77. R. Bise, Z. Yin, and T. Kanade
    Reliable Cell Tracking by Global Data Association Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI)
    pp.1004-1010, 2011.(oral,acceptance rate < 18%)
  78. S. Huh, S. Eom, R. Bise, Z. Yin, and T. Kanade
    Mitosis Detection for Stem Cell Tracking in Phase-Contrast Microscopy Images Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI)
    pages 2121-2127, 2011
  79. T. Kanade, Z. Yin, R. Bise, S. Huh, S. Eom, M. Sandbothe and M. Chen
    Cell Image Analysis: Algorithms, System and Applications Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV)
    pp.374-381, 2011
  80. S. Eom, R. Bise, and T. Kanade
    Detection of Hematopoietic Stem Cells in Microscopy Images Using a Bank of Ring Filters Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI)
    pp.137-140, 2010
  81. Z. Yin, R. Bise, M. Chen, and T. Kanade
    Cell Segmentation in Microscopy Imagery Using a Bag of Local Bayesian Classifiers Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI)
    pp.125-128, 2010
  82. R. Bise, K. Li, S. Eom, and T. Kanade
    Reliably Tracking Partially Overlapping Neural Stem Cells in DIC Microscopy Image Sequences Proceedings of MICCAI Workshop on OPTMHisE
    pp.67-77, 2009
  83. R Bise, N Takahashi, T Nishi
    An improvement of the design method of cellular neural networks based on generalized eigenvalue minimization
    IEEE Trans. Circuits and Systems I: Fundamental Theory and Applications, 50(12), 1569-1574, 2013 (IF:2.303)
  84. R. Bise, N. Takahashi, and T. Nishi
    On the design method of cellular neural networks for associative memories based on generalized eigenvalue problem Proceedings of IEEE Cellular Neural Networks and Their Applications
    pp.515-522, 2002


Presentations in International Conference
  1. Dan Wang, Xu Zhang, Kazuya Nishimura, Rocky Tuan, Ryoma Bise, Dai Fei Elmer Ker
    Label-Free Cell Detection in Phase Contrast Images Using Artificial Neural Networks
    Orthopaedic Research Society (ORS) Annual Meeting, 2020.3.
  2. Junya Hayashida, Ryoma Bise
    Cell Tracking by estimating cell motions for high-throughput screening
    In Resonance Bio International Symposium, Japan, November 2019.
  3. Nishimura Kazuya, Dai Fei Elmer Ker, Ryoma Bise
    Deep learning for cell segmentation with less annotation
    In Resonance Bio International Symposium, Japan, November 2019.
  4. Kentaro Abe, Hideaki Hayashi, Ryoma Bise, Takuji Kawamura, Naokuni Sakiyama, Kiyohito Tanaka, Seiichi Uchida
    Clustering of Colonoscopic Image with Multi-Task Learning
    The 15th Joint Workshop on Machine Perception and Robotics (MPR2019), Shiga, Japan, 2019.11.
  5. Ryo Kikkawa, Ryoma Bise
    Weakly Supervised Body Hair Detection in Photoacoustic Image
    The 15th Joint Workshop on Machine Perception and Robotics (MPR2019), Shiga, Japan, 2019.11.
  6. Nishimura Kazuya, Dai Fei Elmer Ker, Ryoma Bise
    Weakly supervised Cell Segmentation
    The 15th Joint Workshop on Machine Perception and Robotics (MPR2019), Shiga, Japan, 2019.11.
  7. Junya Hayashida, Ryoma Bise
    Cell Tracking with CNN for Cell Detection and Association
    The 15th Joint Workshop on Machine Perception and Robotics (MPR2019), Shiga, Japan, 2019.11.
  8. Yuki Teramoto, Akihiko Yoshizawa, Ryoma Bise, Hiroki Tokunaga, Naoki Nakajima, and Hironori Haga
    Deep learning for cell segmentation with less annotation
    United States & Canadian Academy of Pathology Annual Meeting (USCAP 2019), March 2019 (Poster presentation，査読有り)
  9. Matsumoto Y, Gu L, Bise R, Asao Y, Sekiguchi H, Yoshikawa A, Ishii T, Takada M, Kataoka M, Sakurai T, Yagi T, Sato I, Togashi K, Shiina T, and Toi M.
    Machine learning-based structural analysis and oxygen saturation measurement of tumor-associated vessels in breast cancer using a photoacoustic tomography system
    USA, San Antonio Breast Cancer Symposium 2018.
  10. K.Kajiya, R.Bise, C.Seidel, I. Sato, T. Yamashita, and M. Detmar
    Cleaning of a human skin and its application for the three-dimensional visualization of the vasculature
    Journal of Investigative Dermatology, 136, 9, S254, 2016.
  11. A. Kondow, K. Ohnuma, S. Nonaka, Y. Kamei, R. Bise, Y. Sato, T. Kobayashi, and K. Hashimoto
    In vivo measurement of the Nodal signal followed by 3D tracking during early zebrafish development
    JSDB Special Symposium: Frontier of Developmental Biology, June 2016.
  12. R. Bise et al.
    3D Cell Tracking Under Dense Cell Culture Conditions by Preserving the Structure of Neighbor Cells
    IEEE International Symposium on Biomedical Imaging(ISBI) 2014
  13. R. Bise et al.
    Cell Image Analysis Technology Applications
    Bioimage Informatics 2010
  14. R. Bise et al.
    Real-time System for Microscope Imaging, Cell Tracking, and Adaptive Culturing
    Bioimage Informatics 2010 (Poster)
  15. R. Bise and T. Akai
    Cell Migration Assay Kit based on Smart Surface and Cell Tracking
    First Workshop on Computer Vision Tracking of Cell Populations 2011 (oral)
  16. R. Bise, Z. Yin, S. Huh, S. Eom, and T. Kanade
    Global Tree Structure Association Method for Tracking Cells and Creating Lineage Tree
    First Workshop on Computer Vision Tracking of Cell Populations 2011 (Poster)
  17. E.D.F. Ker, L. Weiss, S. Junkers, M. Chen, Z. Yin, E. Highley, S. Huh, M.F. Sandbothe, S. Eom, R. Bise, T. Kanade, and P. Campbell
    Towards Robotic Subculture of Cells: Automating the Decision Process for Real Time Adaptive Subculture of Stem Cells
    First Workshop on Computer Vision Tracking of Cell Populations 2011 (Poster)
  18. T. Kanade, M.F. Sandbothe, D.F.E. Ker, S. Eom, R. Bise, S.Huh, Z. Yin, and M. Chen
    Real-time System for Microscope Imaging, Cell Tracking, and Adaptive Culturing
    Bioimage informatics, 2010, (Poster)
  19. T. Kanade, S. Eom, R. Bise, Seung-il Huh, Zhaozheng Yin, and Mei Chen
    Cell Image Analysis Technology Applications
    Bioimage informatics, 2010, (Poster)
  20. R. Bise, Kang Li, and Takeo Kanade
    Cell Tracking with Occlusion Handling
    ntel Labs Pittsburgh Open House 2009
  21. R. Bise, K. Li, and T. Kanade
    Automated Stem Cell Tracking through Long-Term Partial Overlap
    Annual meeting of Biomedical Engineering Society(BMES), 2009


Ph.D. Thesis
  1. Ryoma Bise
    Cell Tracking Under Dense Cell Culture Conditions for Cell Behavior Analysis
    Graduate School of Interdisciplinary Information Studies, The University of Tokyo, 2015.05