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Bridging Medical Imaging and Reports:Learning Radiologist's Nuances via Fine-Grained Multi-Modal Alignment

2025-03-25

Abstract excerpt

<title>Abstract</title> <p>Precise and explainable alignment between data from different data modalities is crucial for advancing artificial general intelligence in medicine. In this work, we present CAMMAL (Cyclic Adaptive Medical Modality ALignment), a framework that can achieve fine-grained vision-language alignment through two key innovations, including an Adaptive Patch-Word Matching (AdaMatch) mechanism tha...

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Literature Corpus work: 359b4fda-e64d-5451-9663-acb29b9b29c1
DOI: 10.21203/rs.3.rs-6002276/v1

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