RoboEM: automated 3D flight tracing for synaptic-resolution connectomics

Abstract

ABSTRACTMapping neuronal networks from 3-dimensional electron microscopy data still poses substantial reconstruction challenges, in particular for thin axons. Currently available automated image segmentation methods, while substantially progressed, still require human proof reading for many types of connectomic analyses. RoboEM, an AI-based self-steering 3D flight system trained to navigate along neurites using only EM data as input, substantially improves automated state-of-the-art segmentations and replaces human proof reading for more complex connectomic analysis problems, yielding computational annotation cost for cortical connectomes about 400-fold lower than the cost of manual error correction.