Title: "Connectomics: Extracting Neural Connectivity From Very Large Data Sets"

Connectomics is the study of neural connectivity. Using images from electron microscopes, we automatically identify nanometer-scale structures in microtomed brain tissue. We work with slices and images at a resolution where a cubic sample one millimeter on a side produces more than one petabyte of image data.
To deal with such large datasets requires a mostly-automated approach. Our analysis pipeline uses computer vision, machine learning, and cluster computing to produce an initial version of the connectome within a sample. We then use a web-based proofreading and annotation tool to allow multiple simultaneous users to explore and correct the data within the volume.