A 3D CT vision-language pretraining framework with global and organ-level contrastive alignment plus a text retrieval bank achieves state-of-the-art zero-shot disease classification, report retrieval, and medical visual question answering on CT-RATE and Rad-ChestCT.
Joint modeling of chest radiographs and radiology reports for pulmonary edema assessment
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MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting
A 3D CT vision-language pretraining framework with global and organ-level contrastive alignment plus a text retrieval bank achieves state-of-the-art zero-shot disease classification, report retrieval, and medical visual question answering on CT-RATE and Rad-ChestCT.