How to build the best medical image segmentation algorithm using foundation models: a comprehensive empirical study with Segment Anything Model

arXiv:2404.09957v1 Announce Type: cross
Abstract: Automated segmentation is a fundamental medical image analysis task, which enjoys significant advances due to the advent of deep learning. While foundation models have been useful in natural language processing and some vision tasks for some time, the foundation model developed with image segmentation in mind - Segment Anything Model (SAM) - has been developed only recently and has shown similar promise. However, there are still no systematic analyses or ``best-practice'' guidelines for optimal fine-tuning …

algorithm arxiv build cs.cv cs.lg foundation image medical segment segment anything segment anything model segmentation study type