Multi-View Hypercomplex Learning for Breast Cancer Screening
Radiologists interpret mammography exams by jointly analyzing all four views, as correlations among them are crucial for an accurate diagnosis. Recent methods have employed dedicated fusion blocks to capture such dependencies, but these are often hindered by view dominance, training instability, and...
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| Главные авторы: | , , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
IEEE
2026-01-01
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| Серии: | IEEE Access |
| Предметы: | |
| Online-ссылка: | https://ieeexplore.ieee.org/document/11494775/ |
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