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Ryoma Bise
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2020 – today
- 2024
- [j9]Xiaoqing Liu, Kenji Ono, Ryoma Bise:
A data augmentation approach that ensures the reliability of foregrounds in medical image segmentation. Image Vis. Comput. 147: 105056 (2024) - [j8]Takeaki Kadota
, Hideaki Hayashi
, Ryoma Bise
, Kiyohito Tanaka, Seiichi Uchida
:
Deep Bayesian active learning-to-rank with relative annotation for estimation of ulcerative colitis severity. Medical Image Anal. 97: 103262 (2024) - [c46]Kaito Shiku, Shinnosuke Matsuo, Daiki Suehiro, Ryoma Bise:
Counting Network for Learning from Majority Label. ICASSP 2024: 7025-7029 - [i24]Kaito Shiku, Shinnosuke Matsuo, Daiki Suehiro, Ryoma Bise:
Counting Network for Learning from Majority Label. CoRR abs/2403.13370 (2024) - [i23]Kaito Shiku, Hiromitsu Shirai, Takeshi Ishihara, Ryoma Bise:
Cell Tracking in C. elegans with Cell Position Heatmap-Based Alignment and Pairwise Detection. CoRR abs/2403.13412 (2024) - [i22]Takumi Okuo, Kazuya Nishimura, Hiroaki Ito, Kazuhiro Terada, Akihiko Yoshizawa, Ryoma Bise:
Proportion Estimation by Masked Learning from Label Proportion. CoRR abs/2405.04815 (2024) - [i21]Shinnosuke Matsuo, Daiki Suehiro, Seiichi Uchida, Hiroaki Ito, Kazuhiro Terada, Akihiko Yoshizawa, Ryoma Bise:
Learning from Partial Label Proportions for Whole Slide Image Segmentation. CoRR abs/2405.09041 (2024) - 2023
- [c45]Kaito Shiku, Hiromitsu Shirai, Takeshi Ishihara, Ryoma Bise:
Cell Tracking in C. elegans with Cell Position Heatmap-Based Alignment and Pairwise Detection. EMBC 2023: 1-4 - [c44]Shinnosuke Matsuo, Ryoma Bise, Seiichi Uchida, Daiki Suehiro:
Learning From Label Proportion with Online Pseudo-Label Decision by Regret Minimization. ICASSP 2023: 1-5 - [c43]Takanori Asanomi, Shinnosuke Matsuo, Daiki Suehiro, Ryoma Bise:
MixBag: Bag-Level Data Augmentation for Learning from Label Proportions. ICCV 2023: 16524-16533 - [c42]Shota Harada, Ryoma Bise, Kengo Araki, Akihiko Yoshizawa, Kazuhiro Terada, Mariyo Kurata, Naoki Nakajima, Hiroyuki Abe, Tetsuo Ushiku, Seiichi Uchida:
Cluster-Guided Semi-Supervised Domain Adaptation for Imbalanced Medical Image Classification. ISBI 2023: 1-5 - [c41]Xiaoqing Liu, Kengo Araki, Shota Harada, Akihiko Yoshizawa, Kazuhiro Terada, Mariyo Kurata, Naoki Nakajima, Hiroyuki Abe, Tetsuo Ushiku, Ryoma Bise:
Cluster Entropy: Active Domain Adaptation in Pathological Image Segmentation. ISBI 2023: 1-5 - [c40]Xiaoqing Liu, Kenji Ono, Ryoma Bise:
Mixing Data Augmentation with Preserving Foreground Regions in Medical Image Segmentation. ISBI 2023: 1-5 - [c39]Yuki Shigeyasu, Kengo Araki, Shota Harada, Akihiko Yoshizawa, Kazuhiro Terada, Ryoma Bise:
Spatial Distribution-Based Pseudo Labeling for Pathological Image Segmentation. ISBI 2023: 1-5 - [c38]Takumi Okuo, Kazuya Nishimura, Hiroaki Ito, Kazuhiro Terada, Akihiko Yoshizawa, Ryoma Bise:
Proportion Estimation by Masked Learning from Label Proportion. DALI@MICCAI 2023: 117-126 - [c37]Kazuya Nishimura, Ami Katanaya, Shinichiro Chuma, Ryoma Bise:
Mitosis Detection from Partial Annotation by Dataset Generation via Frame-Order Flipping. MICCAI (8) 2023: 483-492 - [c36]Takanori Asanomi, Kazuya Nishimura, Ryoma Bise:
Multi-Frame Attention with Feature-Level Warping for Drone Crowd Tracking. WACV 2023: 1664-1673 - [c35]Kazuya Nishimura, Ryoma Bise:
Weakly Supervised Cell-Instance Segmentation with Two Types of Weak Labels by Single Instance Pasting. WACV 2023: 3184-3193 - [i20]Shinnosuke Matsuo, Ryoma Bise, Seiichi Uchida, Daiki Suehiro:
Learning from Label Proportion with Online Pseudo-Label Decision by Regret Minimization. CoRR abs/2302.08947 (2023) - [i19]Shota Harada, Ryoma Bise, Kengo Araki, Akihiko Yoshizawa, Kazuhiro Terada, Mariyo Rokutan-Kurata, Naoki Nakajima, Hiroyuki Abe, Tetsuo Ushiku, Seiichi Uchida:
Cluster-Guided Semi-Supervised Domain Adaptation for Imbalanced Medical Image Classification. CoRR abs/2303.01283 (2023) - [i18]Hyeonwoo Cho, Kazuya Nishimura, Kazuhide Watanabe, Ryoma Bise:
Effective Pseudo-Labeling based on Heatmap for Unsupervised Domain Adaptation in Cell Detection. CoRR abs/2303.05269 (2023) - [i17]Xiaoqing Liu, Kenji Ono, Ryoma Bise:
Mixing Data Augmentation with Preserving Foreground Regions in Medical Image Segmentation. CoRR abs/2304.13490 (2023) - [i16]Xiaoqing Liu, Kengo Araki, Shota Harada, Akihiko Yoshizawa, Kazuhiro Terada, Mariyo Kurata, Naoki Nakajima, Hiroyuki Abe, Tetsuo Ushiku, Ryoma Bise:
Cluster Entropy: Active Domain Adaptation in Pathological Image Segmentation. CoRR abs/2304.13513 (2023) - [i15]Kazuya Nishimura, Ami Katanaya, Shinichiro Chuma, Ryoma Bise:
Mitosis Detection from Partial Annotation by Dataset Generation via Frame-Order Flipping. CoRR abs/2307.04113 (2023) - [i14]Takanori Asanomi, Shinnosuke Matsuo, Daiki Suehiro, Ryoma Bise:
MixBag: Bag-Level Data Augmentation for Learning from Label Proportions. CoRR abs/2308.08822 (2023) - 2022
- [j7]Takeaki Kadota
, Kentaro Abe, Ryoma Bise
, Takuji Kawamura, Naokuni Sakiyama, Kiyohito Tanaka, Seiichi Uchida
:
Automatic Estimation of Ulcerative Colitis Severity by Learning to Rank With Calibration. IEEE Access 10: 25688-25695 (2022) - [j6]Hyeonwoo Cho, Kazuya Nishimura, Kazuhide Watanabe
, Ryoma Bise
:
Effective pseudo-labeling based on heatmap for unsupervised domain adaptation in cell detection. Medical Image Anal. 79: 102436 (2022) - [j5]Hiroki Okawa
, Mihoko Shimano, Yuta Asano
, Ryoma Bise
, Ko Nishino
, Imari Sato:
Estimation of Wetness and Color from a Single Multispectral Image. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 8740-8753 (2022) - [c34]Tatsuhiko Sugimoto, Hiroaki Ito, Yuki Teramoto, Akihiko Yoshizawa, Ryoma Bise:
Multi-Class Cell Detection Using Modified Self-Attention. CVPR Workshops 2022: 1854-1862 - [c33]Takanori Asanomi, Kazuya Nishimura, Heon Song, Junya Hayashida, Hiroyuki Sekiguchi, Takayuki Yagi, Imari Sato, Ryoma Bise:
Unsupervised Deep Non-rigid Alignment by Low-Rank Loss and Multi-input Attention. MICCAI (6) 2022: 185-195 - [c32]Takeaki Kadota
, Hideaki Hayashi
, Ryoma Bise, Kiyohito Tanaka, Seiichi Uchida:
Deep Bayesian Active-Learning-to-Rank for Endoscopic Image Data. MIUA 2022: 609-622 - [c31]Junya Hayashida, Kazuya Nishimura, Ryoma Bise:
Consistent Cell Tracking in Multi-frames with Spatio-Temporal Context by Object-Level Warping Loss. WACV 2022: 1759-1768 - [i13]Takeaki Kadota, Hideaki Hayashi, Ryoma Bise, Kiyohito Tanaka, Seiichi Uchida:
Deep Bayesian Active-Learning-to-Rank for Endoscopic Image Data. CoRR abs/2208.03020 (2022) - 2021
- [j4]Shota Harada, Ryoma Bise, Hideaki Hayashi
, Kiyohito Tanaka, Seiichi Uchida:
Soft and self constrained clustering for group-based labeling. Medical Image Anal. 72: 102097 (2021) - [j3]Kazuya Nishimura, Chenyang Wang, Kazuhide Watanabe, Dai Fei Elmer Ker, Ryoma Bise:
Weakly supervised cell instance segmentation under various conditions. Medical Image Anal. 73: 102182 (2021) - [c30]Kengo Araki, Mariyo Rokutan-Kurata, Kazuhiro Terada, Akihiko Yoshizawa, Ryoma Bise:
Patch-Based Cervical Cancer Segmentation using Distance from Boundary of Tissue. EMBC 2021: 3328-3331 - [c29]Ryo Kikkawa, Hiroki Kajita, Nobuaki Imanishi, Sadakazu Aiso, Ryoma Bise:
Unsupervised Body Hair Detection by Positive-Unlabeled Learning in Photoacoustic Image. EMBC 2021: 3349-3352 - [c28]Kazuya Nishimura, Hyeonwoo Cho, Ryoma Bise:
Semi-supervised Cell Detection in Time-Lapse Images Using Temporal Consistency. MICCAI (8) 2021: 373-383 - [c27]Hyeonwoo Cho, Kazuya Nishimura, Kazuhide Watanabe, Ryoma Bise:
Cell Detection in Domain Shift Problem Using Pseudo-Cell-Position Heatmap. MICCAI (8) 2021: 384-394 - [c26]Kazuma Fujii, Daiki Suehiro, Kazuya Nishimura, Ryoma Bise:
Cell Detection from Imperfect Annotation by Pseudo Label Selection Using P-classification. MICCAI (8) 2021: 425-434 - [c25]Shota Harada, Ryoma Bise, Hideaki Hayashi
, Kiyohito Tanaka, Seiichi Uchida:
Order-Guided Disentangled Representation Learning for Ulcerative Colitis Classification with Limited Labels. MICCAI (2) 2021: 471-480 - [i12]Kazuya Nishimura, Hyeonwoo Cho, Ryoma Bise:
Semi-supervised Cell Detection in Time-lapse Images Using Temporal Consistency. CoRR abs/2107.08639 (2021) - [i11]Hyeonwoo Cho, Kazuya Nishimura, Kazuhide Watanabe, Ryoma Bise:
Cell Detection in Domain Shift Problem Using Pseudo-Cell-Position Heatmap. CoRR abs/2107.08653 (2021) - [i10]Kazuma Fujii, Daiki Suehiro, Kazuya Nishimura, Ryoma Bise:
Cell Detection from Imperfect Annotation by Pseudo Label Selection Using P-classification. CoRR abs/2107.09289 (2021) - [i9]Kengo Araki, Mariyo Rokutan-Kurata, Kazuhiro Terada, Akihiko Yoshizawa, Ryoma Bise:
Patch-Based Cervical Cancer Segmentation using Distance from Boundary of Tissue. CoRR abs/2108.08508 (2021) - [i8]Shota Harada, Ryoma Bise, Hideaki Hayashi, Kiyohito Tanaka, Seiichi Uchida:
Order-Guided Disentangled Representation Learning for Ulcerative Colitis Classification with Limited Labels. CoRR abs/2111.03815 (2021) - 2020
- [c24]Junya Hayashida, Kazuya Nishimura, Ryoma Bise:
MPM: Joint Representation of Motion and Position Map for Cell Tracking. CVPR 2020: 3822-3831 - [c23]Kazuya Nishimura, Junya Hayashida, Chenyang Wang, Dai Fei Elmer Ker, Ryoma Bise:
Weakly-Supervised Cell Tracking via Backward-and-Forward Propagation. ECCV (12) 2020: 104-121 - [c22]Hiroki Tokunaga, Brian Kenji Iwana, Yuki Teramoto, Akihiko Yoshizawa, Ryoma Bise:
Negative Pseudo Labeling Using Class Proportion for Semantic Segmentation in Pathology. ECCV (15) 2020: 430-446 - [c21]Kazuya Nishimura, Ryoma Bise:
Spatial-Temporal Mitosis Detection in Phase-Contrast Microscopy via Likelihood Map Estimation by 3DCNN. EMBC 2020: 1811-1815 - [c20]Mihoko Shimano, Yuta Asano
, Shin Ishihara, Ryoma Bise, Imari Sato:
Imaging Scattering Characteristics of Tissue in Transmitted Microscopy. MICCAI (5) 2020: 236-245 - [i7]Junya Hayashida, Kazuya Nishimura, Ryoma Bise:
MPM: Joint Representation of Motion and Position Map for Cell Tracking. CoRR abs/2002.10749 (2020) - [i6]Kazuya Nishimura, Ryoma Bise:
Spatial-Temporal Mitosis Detection in Phase-Contrast Microscopy via Likelihood Map Estimation by 3DCNN. CoRR abs/2004.12531 (2020) - [i5]Hiroki Tokunaga, Brian Kenji Iwana, Yuki Teramoto, Akihiko Yoshizawa, Ryoma Bise:
Negative Pseudo Labeling using Class Proportion for Semantic Segmentation in Pathology. CoRR abs/2007.08044 (2020) - [i4]Kazuya Nishimura, Junya Hayashida, Chenyang Wang, Dai Fei Elmer Ker, Ryoma Bise:
Weakly-Supervised Cell Tracking via Backward-and-Forward Propagation. CoRR abs/2007.15258 (2020)
2010 – 2019
- 2019
- [c19]Hiroki Tokunaga, Yuki Teramoto, Akihiko Yoshizawa, Ryoma Bise:
Adaptive Weighting Multi-Field-Of-View CNN for Semantic Segmentation in Pathology. CVPR 2019: 12597-12606 - [c18]Daisuke Harada, Ryoma Bise, Hiroki Tokunaga, Wataru Ohyama, Sanae Oka, Toshihiko Fujimori, Seiichi Uchida:
Scribbles for Metric Learning in Histological Image Segmentation. EMBC 2019: 1026-1030 - [c17]Shota Harada, Hideaki Hayashi, Ryoma Bise, Kiyohito Tanaka, Qier Meng, Seiichi Uchida:
Endoscopic Image Clustering with Temporal Ordering Information Based on Dynamic Programming. EMBC 2019: 3681-3684 - [c16]Ryo Kikkawa, Hiroyuki Sekiguchi, Itaru Tsuge, Susumu Saito, Ryoma Bise:
Semi-Supervised Learning With Structured Knowledge For Body Hair Detection In Photoacoustic Image. ISBI 2019: 1411-1415 - [c15]Junya Hayashida, Ryoma Bise:
Cell Tracking with Deep Learning for Cell Detection and Motion Estimation in Low-Frame-Rate. MICCAI (1) 2019: 397-405 - [c14]Ryoma Bise, Kentaro Abe, Hideaki Hayashi, Kiyohito Tanaka, Seiichi Uchida:
Efficient Soft-Constrained Clustering for Group-Based Labeling. MICCAI (5) 2019: 421-430 - [c13]Kazuya Nishimura, Dai Fei Elmer Ker, Ryoma Bise:
Weakly Supervised Cell Instance Segmentation by Propagating from Detection Response. MICCAI (1) 2019: 649-657 - [i3]Hiroki Tokunaga, Yuki Teramoto, Akihiko Yoshizawa, Ryoma Bise:
Adaptive Weighting Multi-Field-of-View CNN for Semantic Segmentation in Pathology. CoRR abs/1904.06040 (2019) - [i2]Kazuya Nishimura, Dai Fei Elmer Ker, Ryoma Bise:
Weakly Supervised Cell Instance Segmentation by Propagating from Detection Response. CoRR abs/1911.13077 (2019) - 2017
- [c12]Mihoko Shimano, Hiroki Okawa, Yuta Asano
, Ryoma Bise, Ko Nishino, Imari Sato:
Wetness and Color from a Single Multispectral Image. CVPR 2017: 321-329 - [c11]Qiuyu Chen, Ryoma Bise, Lin Gu, Yinqiang Zheng
, Imari Sato, Jenq-Neng Hwang, Sadakazu Aiso, Nobuaki Imanishi:
Virtual Blood Vessels in Complex Background Using Stereo X-Ray Images. ICCV Workshops 2017: 99-106 - [c10]Mihoko Shimano, Ryoma Bise, Yinqiang Zheng
, Imari Sato:
Separation of Transmitted Light and Scattering Components in Transmitted Microscopy. MICCAI (2) 2017: 12-20 - [c9]Lin Gu, Yinqiang Zheng
, Ryoma Bise, Imari Sato, Nobuaki Imanishi, Sadakazu Aiso:
Semi-supervised Learning for Biomedical Image Segmentation via Forest Oriented Super Pixels(Voxels). MICCAI (1) 2017: 702-710 - [i1]Qiuyu Chen, Ryoma Bise, Lin Gu, Yinqiang Zheng, Imari Sato, Jenq-Neng Hwang, Nobuaki Imanishi, Sadakazu Aiso:
Virtual Blood Vessels in Complex Background using Stereo X-ray Images. CoRR abs/1709.07551 (2017) - 2016
- [c8]Ryoma Bise, Imari Sato, Kentaro Kajiya, Toyonobu Yamashita:
3D Structure Modeling of Dense Capillaries by Multi-objects Tracking. CVPR Workshops 2016: 1333-1341 - [c7]Ryoma Bise, Yingqiang Zheng
, Imari Sato, Masakazu Toi:
Vascular Registration in Photoacoustic Imaging by Low-Rank Alignment via Foreground, Background and Complement Decomposition. MICCAI (3) 2016: 326-334 - 2015
- [j2]Ryoma Bise, Yoichi Sato:
Cell Detection From Redundant Candidate Regions Under Nonoverlapping Constraints. IEEE Trans. Medical Imaging 34(7): 1417-1427 (2015) - 2011
- [j1]Seungil Huh, Dai Fei Elmer Ker
, Ryoma Bise, Mei Chen, Takeo Kanade:
Automated Mitosis Detection of Stem Cell Populations in Phase-Contrast Microscopy Images. IEEE Trans. Medical Imaging 30(3): 586-596 (2011) - [c6]Ryoma Bise, Takeo Kanade, Zhaozheng Yin, Seungil Huh:
Automatic cell tracking applied to analysis of cell migration in wound healing assay. EMBC 2011: 6174-6179 - [c5]Ryoma Bise, Zhaozheng Yin, Takeo Kanade:
Reliable cell tracking by global data association. ISBI 2011: 1004-1010 - [c4]Seungil Huh, Sungeun Eom, Ryoma Bise, Zhaozheng Yin, Takeo Kanade:
Mitosis detection for stem cell tracking in phase-contrast microscopy images. ISBI 2011: 2121-2127 - [c3]Takeo Kanade, Zhaozheng Yin, Ryoma Bise, Seungil Huh, Sungeun Eom, Michael F. Sandbothe, Mei Chen:
Cell image analysis: Algorithms, system and applications. WACV 2011: 374-381 - 2010
- [c2]Zhaozheng Yin, Ryoma Bise, Mei Chen, Takeo Kanade:
Cell segmentation in microscopy imagery using a bag of local Bayesian classifiers. ISBI 2010: 125-128 - [c1]Sungeun Eom, Ryoma Bise, Takeo Kanade:
Detection of hematopoietic stem cells in microscopy images using a bank of ring filters. ISBI 2010: 137-140
Coauthor Index
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last updated on 2024-08-23 18:36 CEST by the dblp team
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