A Comparative Study of Feature Descriptors for Mitochondria and Synapse Segmentation

Full understanding of the architecture of the brain is a long term goal of neuroscience. To achieve it, advanced image processing tools are required, that automate the the analysis and reconstruction of brain structures. Synapses and mitochondria are two prominent structures with neurological interest for which various automated image segmentation approaches have been recently proposed. In this work we present a comparative study of several image feature descriptors used for the segmentation of synapses and mitochondria in stacks of electron microscopy images.