Publications

Kazuya Nishimura (西村 和也)

Journal Papers

  1. Kazuya Nishimura, Chenyang Wang, Kazuhide Watanabe, Dai Fei Elmer Ker, Ryoma Bise, "Weakly Supervised Cell Instance Segmentation under Various Conditions", Medical Image Analysis (MIA), 2021. MIA 2021 [Paper] [Code]

  2. Hyeonwoo Cho, Kazuya Nishimura, Kazuhide Watanabe, Ryoma Bise, "Effective pseudo-labeling based on heatmap for unsupervised domain adaptation in cell detection.", Medical Image Analysis, 79, 102436, 2022. MIA 2022 [Paper]

  3. 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. Modern Pathology 2024

International Conference Papers (Peer-reviewed)

  1. Kazuya Nishimura, Dai Fei Elmer Ker, Ryoma Bise, "Weakly Supervised Cell Instance Segmentation by Propagating from Detection Response", MICCAI, pp.649–657, 2019. MICCAI 2019 (Poster, Early Accept: 16%) [Paper] [Code]

  2. Junya Hayashida, Kazuya Nishimura, Ryoma Bise, "MPM: Joint Representation of Motion and Position Map for Cell Tracking", CVPR, 2020. CVPR 2020 (Oral, Accept: 22%, Oral: 5%) [Paper] [Code]

  3. Kazuya Nishimura, Junya Hayashida, Chenyang Wang, Dai Fei Elmer Ker, Ryoma Bise, "Weakly-Supervised Cell Tracking via Backward-and-Forward Propagation", ECCV, pp.104–121, 2020. ECCV 2020 (Poster, Accept: 26%) [Paper] [Code]

  4. Kazuya Nishimura, Ryoma Bise, "Spatial-Temporal Mitosis Detection in Phase-Contrast Microscopy via Likelihood Map Estimation by 3DCNN", EMBC, 2020. EMBC 2020 [Paper] [Code]

  5. Kazuya Nishimura, Hyeonwoo Cho, Ryoma Bise, "Semi-supervised Cell Detection in Time-lapse Images Using Temporal Consistency", MICCAI, 2021. MICCAI 2021 [Paper] [Code]

  6. Hyeonwoo Cho, Kazuya Nishimura, Kazuhide Watanabe, Ryoma Bise, "Cell Detection in Domain Shift Problem Using Pseudo-Cell-Position Heatmap", MICCAI, 2021. MICCAI 2021 [Paper]

  7. Kazuma Fujii, Daiki Suehiro, Kazuya Nishimura, Ryoma Bise, "Cell Detection from Imperfect Annotation by Pseudo Label Selection Using P-classification", MICCAI, 2021. MICCAI 2021 [Paper]

  8. Junya Hayashida, Kazuya Nishimura, Ryoma Bise, "Consistent Cell Tracking in Multi-Frames With Spatio-Temporal Context by Object-Level Warping Loss", WACV, 2022. WACV 2022 [Paper]

  9. Kazuya Nishimura, Ryoma Bise, "Weakly Supervised Cell-Instance Segmentation With Two Types of Weak Labels by Single Instance Pasting", WACV, 2023. WACV 2023 [Paper]

  10. Takanori Asanomi, Kazuya Nishimura, et al., "Unsupervised Deep Non-rigid Alignment by Low-Rank Loss and Multi-input Attention", MICCAI, 2022. MICCAI 2022

  11. Takanori Asanomi, Kazuya Nishimura, Ryoma Bise, "Multi-Frame Attention With Feature-Level Warping for Drone Crowd Tracking", WACV, 2023. WACV 2023 [Paper]

  12. Kazuya Nishimura, Ami Katanaya, Shinichiro Chuma, Ryoma Bise, "Mitosis Detection from Partial Annotation by Dataset Generation via Frame-Order Flipping", MICCAI, 2023. MICCAI 2023 [Paper]

  13. Takumi Okuo, Kazuya Nishimura, Hiroaki Ito, Kazuhiro Terada, Akihiko Yoshizawa, Ryoma Bise, "Proportion Estimation by Masked Learning from Label Proportion", 4th workshop DALI@MICCAI, 2023. DALI@MICCAI 2023 [Paper]

  14. Kazuya Nishimura, Kuniaki Saito, Tosho Hirasawa, Yoshitaka Ushiku, "Toward Related Work Generation with Structure and Novelty Statement", 4th workshop SDP@ACL, 2024. SDP@ACL 2024

  15. Kazuya Nishimura, Ryoma Bise, Yasuhiro Kojima, "Towards Spatial Transcriptomics-Guided Pathological Image Recognition with Batch-Agnostic Encoder", ISBI, 2025. ISBI 2025

  16. Kaito Shiku, Kazuya Nishimura, Daiki Suehiro, Kiyohito Tanaka, Ryoma Bise, "Ordinal Multiple-instance Learning for Ulcerative Colitis Severity Estimation with Selective Aggregated Transformer", WACV, 2025. WACV 2025

  17. Kazuya Nishimura, Haruka Hirose, Ryoma Bise, Kaito Shiku, Yasuhiro Kojima, "Learning to Relative Expression under Batch Effects and Stochastic Noise in Spatial Transcriptomics", NeurIPS, 2025. NeurIPS 2025

  18. Kaito Shiku, Kazuya Nishimura, Shinnosuke Matsuo, Yasuhiro Kojima, Ryoma Bise, "Auxiliary Gene Learning: Spatial Gene Expression Estimation by Auxiliary Gene Selection", AAAI, 2026. AAAI 2026

  19. Masashi Tahara, Kazuya Nishimura, Shumpei Takezaki, Ryoma Bise, "Bridging the Density Gap: Diffusion Model for Stepwise Generation of Dense Cell Images from Sparse Data", ISBI, 2026. ISBI 2026

  20. Kazuya Nishimura, Ryoma Bise, Shinnosuke Matsuo, Haruka Hirose, Yasuhiro Kojima, "Cell-Type Prototype-Informed Neural Network for Gene Expression Estimation from Pathology Images", CVPR, 2026. CVPR 2026

International Conference Papers (Non-peer-reviewed)

  1. Kazuya Nishimura, Dai Fei Elmer Ker, Ryoma Bise, "Weakly supervised Cell Segmentation", Joint Workshop on Machine Perception and Robotics (MPR), Japan, November 2019. (Oral, Contribution Award)

  2. 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, March 2020. (Poster)

  3. Kazuya Nishimura, Dai Fei Elmer Ker, Ryoma Bise, "Deep learning for cell segmentation with less annotation", Resonance Bio International Symposium, October 2019. (Poster)

Domestic Conference Papers

Domestic presentations in Japan (mostly in Japanese). Please refer to the Japanese page for full details.

  1. K. Nishimura et al., "Weakly-supervised cell segmentation", MIRU, Osaka, Jul. 2019. (MIRU Student Encouragement Award)

  2. K. Nishimura, R. Bise, "Cell segmentation in microscopy images", IEICE Kyushu Branch, Sep. 2018.

  3. K. Nishimura et al., "Cell segmentation via weakly-supervised learning", Cell Diverse Workshop, Feb. 2019.

  4. K. Nishimura et al., "Weakly-supervised cell recognition for multiple cell types", PRMU, May 2019. (Oral)

  5. K. Nishimura et al., "Mitosis detection by 3DCNN", PRMU, Sep. 2019. (Oral, PRMU Best Presentation Award)

  6. K. Nishimura et al., "Weakly-supervised cell tracking", PRMU, May 2020. (Oral, PRMU Best Presentation Award)

  7. K. Nishimura et al., "Weakly-supervised cell tracking", MIRU, Aug. 2020. (Oral, MIRU Student Encouragement Award)

  8. K. Nishimura et al., "Cell detection in time-lapse images via tracking", MIRU, Jul. 2021. (Oral, MIRU Student Encouragement Award)

  9. K. Nishimura, R. Bise, "Cell-instance segmentation via single instance pasting", MIRU, Himeji, Jul. 2022.

  10. K. Nishimura et al., "Mitosis detection from partial annotation", MIRU, Hamamatsu, Jul. 2023.

Awards & Honors

  1. Yamashita Memorial Research Award, 2025.

  2. CVPR 2019 Contest on Mitosis Detection — 2nd Place, Jun. 2019.

  3. PRMU Monthly Best Presentation Award, "Mitosis detection by 3DCNN", Sep. 2019.

  4. PRMU Monthly Best Presentation Award, "Weakly-supervised cell tracking", May 2020.

  5. PRMU Research Mentorship Program Excellence Award, "Weakly-Supervised Cell Tracking via BFP", May 2021.

  6. MIRU Student Encouragement Award, "Weakly-supervised cell segmentation", Jul. 2019.

  7. MIRU Student Encouragement Award, "Weakly-supervised cell tracking", Aug. 2020.

  8. MIRU Student Encouragement Award, "Cell detection via tracking", Jul. 2021.

  9. MPR Contribution Award, 15th Joint Workshop on Machine Perception and Robotics, Oct. 2019.

  10. IEICE Kyushu Branch Academic Encouragement Award, 2021.

  11. Kyushu University Graduate School Outstanding Student Award (11th), 2021.

  12. Kyushu University Student Commendation, 2021.

  13. MIRU 2022 Paper Review Contribution Award, Jul. 2022.

  14. Kyushu University Graduate School Outstanding Student Award (14th), 2023.

Grants

  1. JSPS Research Fellowships for Young Scientists (DC1), "Can deep learning acquire related-task learning ability?", Apr. 2021 – Mar. 2024.

  2. JST ACT-X, "Development of bio-image recognition leveraging related-task learning ability of deep learning", Oct. 2021 – Mar. 2024.

  3. JST ACT-X (Acceleration Phase), "Development of bio-image recognition leveraging related-task learning ability of deep learning", Apr. 2024 – Mar. 2025.

  4. JSPS Research Fellowships for Young Scientists (PD), "Elucidating molecular factors linked to morphological information through integrated analysis of images and omics data", Apr. 2024 – Mar. 2027.