Deep Learning Approaches for Large-Scale 3D Neuron Segmentation

by Dr Suman Saha

Wednesday 17 Sept 2025, 11:30 → 13:00 Europe/Zurich

OHSA/B17

Abstract:
Automated neuron segmentation from large-scale electron microscopy (EM) volumes is a central challenge in brain mapping. In the ALBUM project, we address artifacts such as section loss, folds, and limited z-resolution that hinder segmentation accuracy, with the goal of reconstructing higher-quality 3D volumes. Building on this context, I will present Cross-dimension Affinity Distillation (CAD), a recent method for efficient 3D EM neuron segmentation. CAD leverages lightweight 2D CNNs while distilling inter-section dependencies from a 3D teacher network and introducing feature grafting to enhance knowledge transfer. This strategy achieves state-of-the-art segmentation accuracy at a fraction of the computational cost, offering a promising direction for scalable analysis of EM data.

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