DCS-ST for Classification of Breast Cancer Histopathology Images with Limited Annotations
Fuente:
arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | |
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| _version_ | 1866912363145330688 |
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| author | Suxing, Liu Min, Byungwon |
| author_facet | Suxing, Liu Min, Byungwon |
| contents | Deep learning methods have shown promise in classifying breast cancer histopathology images, but their performance often declines with limited annotated data, a critical challenge in medical imaging due to the high cost and expertise required for annotations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_03204 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | DCS-ST for Classification of Breast Cancer Histopathology Images with Limited Annotations Suxing, Liu Min, Byungwon Computer Vision and Pattern Recognition Artificial Intelligence Deep learning methods have shown promise in classifying breast cancer histopathology images, but their performance often declines with limited annotated data, a critical challenge in medical imaging due to the high cost and expertise required for annotations. |
| title | DCS-ST for Classification of Breast Cancer Histopathology Images with Limited Annotations |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence |
| url | https://arxiv.org/abs/2505.03204 |