General lightweight framework for vision foundation model supporting multi-task and multi-center medical image analysis.

ABSTRACT: The foundation model, trained on extensive and diverse datasets, has shown strong performance across numerous downstream tasks. Nevertheless, its application in the medical domain is significantly hindered by issues such as data volume, heterogeneity, and privacy concerns. Therefore, we propose the Vision Foundation Model General Lightweight (VFMGL) framework, which facilitates the decentralized construction of expert clinical models for various medical tasks. The VFMGL framework transfers general knowledge from large-parameter vision foundation models to construct lightweight, robust expert clinical models tailored to specific medical tasks. Through extensive experiments and analyses across a range of medical tasks and scenarios, we demonstrate that VFMGL achieves superior performance in

SUBMITTER: Lu S 

PROVIDER: S-EPMC11873151 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature