ETSAM: Effectively Segmenting Cell Membranes in cryo-Electron Tomograms.

ABSTRACT: Cryogenic Electron Tomography (cryo-ET) is an emerging experimental technique to visualize cell structures and macromolecules in their native cellular environment. Accurate segmentation of cell structures in cryo-ET tomograms, such as cell membranes, is crucial to advance our understanding of cellular organization and function. However, several inherent limitations in cryo-ET tomograms, including the very low signal-to-noise ratio, missing wedge artifacts from limited tilt angles, and other noise artifacts, collectively hinder the reliable identification and delineation of these structures. In this study, we introduce ETSAM - a two-stage SAM2-based (1) fine-tuned AI model that effectively segments cell membranes in cryo-ET tomograms. It is trained on a diverse dataset comprising 83 experim

SUBMITTER: Selvaraj J 

PROVIDER: S-EPMC12697732 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature