Vision-language foundation model for 3D medical imaging
Jing Wu, Yuli Wang, Zhusi Zhong, Weihua Liao, Natalia A. Trayanova, Zhicheng Jiao, Harrison X. Bai
Abstract
Recent advances in AI, especially vision-language foundation models (VLFMs), show promise in automating radiology report generation from complex 3D medical imaging data. Our review analyzes 23 studies on VLFMs, focusing on model architectures, capabilities, training datasets, and evaluation metrics. We discuss AI’s evolution in radiology, emphasizing the need for diverse datasets and standardized metrics, as challenges remain in producing consistent, high-quality reports.
Topics & Concepts
Foundation (evidence)Computer scienceMedical physicsArtificial intelligenceMedicineHistoryArchaeologyMultimodal Machine Learning ApplicationsAI in cancer detectionImage Retrieval and Classification Techniques