Learning Robust Visual Features in Computed Tomography Enables Efficient Transfer Learning for Clinical Tasks

ArXi:2604.04133v1 Announce Type: cross There is substantial interest in developing artificial intelligence systems to radiologists across tasks ranging from segmentation to report generation. Existing computed tomography (CT) foundation models have largely focused on building generalist vision-language systems capable of tasks such as question answering and report generation. However