Connectomes are dense graphs of connections in the brain where each node is a neuron and each edge is a synapse. Several different brain imaging techniques can be used to build connectomes. Electron microscopy (EM), for instance, can produce extremely high resolution volumes of brain images that are able to capture every neuron and synapse in the brain. Image processing is required not only to find each neuron and synapse, but also to connect neurons spanning several images in the volume. One way to track these neurons is to find the tube-shaped axoplasmic reticula (AR) that are present in every neuron (SNH14, SNH13) and track the AR through the volume. Each connected strand of AR indicates one neuron.
[SNH14] A Sinha, WG Roncal, N Kasthuri, JW Lichtman, R Burns. “Automatic Annotation of 3D Axoplasmic Reticula for Neuron Segmentation”, Proceedings in Brain Connectivity, Vol. 4(9): pp. A26, Resting State Brain Connectivity, Boston/Cambridge, MA (November 21, 2014)
[SNH13] A Sinha, WG Roncal, N Kasthuri, JW Lichtman, R Burns, M Kazhdan. “Automatic Annotation of Axoplasmic Reticula in Pursuit of Connectomes using High Resolution Neural EM Data”, Hopkins Imaging Conference, Baltimore, MD (November 21, 2013)