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Accurately estimating the wiring diagram of a brain, known as a connectome,at an ultrastructure level is an open research problem. Specifically, preciselytracking neural processes is difficult, especially across many image slices.Here, we propose a novel method to automatically identify and annotate smallsubcellular structures present in axons, known as axoplasmic reticula, througha 3D volume of high-resolution neural electron microscopy data. Our methodproduces high precision annotations, which can help improve automaticsegmentation by using our results as seeds for segmentation, and as cues to aidsegment merging.

Automatic Annotation of Axoplasmic Reticula in Pursuit of Connectomes using High-Resolution Neural EM Data