AGSAM: Agent-Guided Segment Anything Model for Automatic Segmentation in Few-Shot Scenarios.

ABSTRACT: Precise medical image segmentation of regions of interest (ROIs) is crucial for accurate disease diagnosis and progression assessment. However, acquiring high-quality annotated data at the pixel level poses a significant challenge due to the resource-intensive nature of this process. This scarcity of high-quality annotated data results in few-shot scenarios, which are highly prevalent in clinical applications. To address this obstacle, this paper introduces Agent-Guided SAM (AGSAM), an innovative approach that transforms the Segment Anything Model (SAM) into a fully automated segmentation method by automating prompt generation. Capitalizing on the pre-trained feature extraction and decoding capabilities of SAM-Med2D, AGSAM circumvents the need for manual prompt engineering, ensuring adapta

SUBMITTER: Zhou H 

PROVIDER: S-EPMC11118214 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature