NEURD offers automated proofreading and feature extraction for connectomics.

ABSTRACT: We are in the era of millimetre-scale electron microscopy volumes collected at nanometre resolution^1,2. Dense reconstruction of cellular compartments in these electron microscopy volumes has been enabled by recent advances in machine learning^3-6. Automated segmentation methods produce exceptionally accurate reconstructions of cells, but post hoc proofreading is still required to generate large connectomes that are free of merge and split errors. The elaborate 3D meshes of neurons in these volumes contain detailed morphological information at multiple scales, from the diameter, shape and branching patterns of axons and dendrites, down to the fine-scale structure of dendritic spines. However, extracting these features can require substantial effort to piece together exi

SUBMITTER: Celii B 

PROVIDER: S-EPMC11981913 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature