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Mammo-CLIP: Leveraging Contrastive Language-Image Pre-training (CLIP) for Enhanced Breast Cancer Diagnosis with Multi-view Mammography
April 25, 2024, 7:45 p.m. | Xuxin Chen, Yuheng Li, Mingzhe Hu, Ella Salari, Xiaoqian Chen, Richard L. J. Qiu, Bin Zheng, Xiaofeng Yang
cs.CV updates on arXiv.org arxiv.org
Abstract: Although fusion of information from multiple views of mammograms plays an important role to increase accuracy of breast cancer detection, developing multi-view mammograms-based computer-aided diagnosis (CAD) schemes still faces challenges and no such CAD schemes have been used in clinical practice. To overcome the challenges, we investigate a new approach based on Contrastive Language-Image Pre-training (CLIP), which has sparked interest across various medical imaging tasks. By solving the challenges in (1) effectively adapting the single-view …
abstract accuracy arxiv cad cancer cancer detection cancer diagnosis challenges clinical clip computer cs.ai cs.cv detection diagnosis eess.iv fusion image information language mammography multiple practice pre-training role training type view
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