Multi-Scale Representation of Follicular Lymphoma Pathology Images in a Single Hyperbolic Space
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arXiv
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| Format: | Preprint |
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2025
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| author | Taguchi, Kei Ohara, Kazumasa Yokota, Tatsuya Miyoshi, Hiroaki Hashimoto, Noriaki Takeuchi, Ichiro Hontani, Hidekata |
| author_facet | Taguchi, Kei Ohara, Kazumasa Yokota, Tatsuya Miyoshi, Hiroaki Hashimoto, Noriaki Takeuchi, Ichiro Hontani, Hidekata |
| contents | We propose a method for representing malignant lymphoma pathology images, from high-resolution cell nuclei to low-resolution tissue images, within a single hyperbolic space using self-supervised learning. To capture morphological changes that occur across scales during disease progression, our approach embeds tissue and corresponding nucleus images close to each other based on inclusion relationships. Using the Poincaré ball as the feature space enables effective encoding of this hierarchical structure. The learned representations capture both disease state and cell type variations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_18523 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Multi-Scale Representation of Follicular Lymphoma Pathology Images in a Single Hyperbolic Space Taguchi, Kei Ohara, Kazumasa Yokota, Tatsuya Miyoshi, Hiroaki Hashimoto, Noriaki Takeuchi, Ichiro Hontani, Hidekata Computer Vision and Pattern Recognition We propose a method for representing malignant lymphoma pathology images, from high-resolution cell nuclei to low-resolution tissue images, within a single hyperbolic space using self-supervised learning. To capture morphological changes that occur across scales during disease progression, our approach embeds tissue and corresponding nucleus images close to each other based on inclusion relationships. Using the Poincaré ball as the feature space enables effective encoding of this hierarchical structure. The learned representations capture both disease state and cell type variations. |
| title | Multi-Scale Representation of Follicular Lymphoma Pathology Images in a Single Hyperbolic Space |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2506.18523 |