biostudies-literatureZhao YNIGMS NIH HHS124-134https://www.ebi.ac.uk/biostudies/studies/S-EPMC12923679biostudies-literatureUnknown15008Cryogenic Electron Tomography (CryoET) is a useful imaging technology in structural biology that is hindered by its need for manual annotations, especially in particle picking. Recent works have endeavored to remedy this issue with few-shot learning or contrastive learning techniques. However, supervised training is still inevitable for them. We instead choose to leverage the power of existing 2D foundation models and present a novel, training-free framework, CryoSAM. In addition to prompt-based single-particle instance segmentation, our approach can automatically search for similar features, facilitating full tomogram semantic segmentation with only one prompt. CryoSAM is composed of two major parts: 1) a prompt-based 3D segmentation system that uses prompts to complete single-particle inMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted InterventionCryoSAM: Training-free CryoET Tomogram Segmentation with Foundation Models.PMC12923679R01 GM134020P41 GM103712Mu MLi XLi ZXu MWang TBian HUddin MRZhao YfalseCryoSAM: Training-free CryoET Tomogram Segmentation with Foundation Models.Cryogenic Electron Tomography (CryoET) is a useful imaging technology in structural biology that is hindered by its need for manual annotations, especially in particle picking. Recent works have endeavored to remedy this issue with few-shot learning or contrastive learning techniques. However, supervised training is still inevitable for them. We instead choose to leverage the power of existing 2D foundation models and present a novel, training-free framework, CryoSAM. In addition to prompt-based single-particle instance segmentation, our approach can automatically search for similar features, facilitating full tomogram semantic segmentation with only one prompt. CryoSAM is composed of two major parts: 1) a prompt-based 3D segmentation system that uses prompts to complete single-particle in2024-01-01T00:00:00Z2024 Oct2026-07-09T12:26:54.629Z2026-07-09T11:17:41.474ZS-EPMC129236794172657310.1007/978-3-031-72111-3_12