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.
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