CryoVesNet: A dedicated framework for synaptic vesicle segmentation in cryo-electron tomograms.

ABSTRACT: Cryo-electron tomography (cryo-ET) has the potential to reveal cell structure down to atomic resolution. Nevertheless, cellular cryo-ET data is highly complex, requiring image segmentation for visualization and quantification of subcellular structures. Due to noise and anisotropic resolution in cryo-ET data, automatic segmentation based on classical computer vision approaches usually does not perform satisfactorily. Communication between neurons relies on neurotransmitter-filled synaptic vesicle (SV) exocytosis. Cryo-ET study of the spatial organization of SVs and their interconnections allows a better understanding of the mechanisms of exocytosis regulation. Accurate SV segmentation is a prerequisite to obtaining a faithful connectivity representation. Hundreds of SVs are present in a syn

SUBMITTER: Khosrozadeh A 

PROVIDER: S-EPMC11513246 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature