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Anatomy-Aware Contrastive Representation Learning for Fetal Ultrasound
Self-supervised contrastive representation learning offers the advantage of learning meaningful visual representations from unlabeled medical datasets for transfer learning. However, applying current contrastive learning approaches to medical data without considering its domain-specific anatomical c...
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| 出版年: | Comput Vis ECCV |
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| 主要な著者: | , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2022
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7614575/ https://ncbi.nlm.nih.gov/pubmed/37250853 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-031-25066-8_23 |
| タグ: |
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