학술논문

A Multiscale Parallel Computing Architecture for Automated Segmentation of the Brain Connectome
Document Type
Periodical
Source
IEEE Transactions on Biomedical Engineering IEEE Trans. Biomed. Eng. Biomedical Engineering, IEEE Transactions on. 59(1):35-38 Jan, 2012
Subject
Bioengineering
Computing and Processing
Components, Circuits, Devices and Systems
Communication, Networking and Broadcast Technologies
Image segmentation
Three dimensional displays
Shape
Computer architecture
Microscopy
Brain
Visualization
Brain anatomy
circuit connectome
computational architecture
data-intensive computing
electron microscopy
image segmentation
multiscale analysis
parallel computing
Language
ISSN
0018-9294
1558-2531
Abstract
Several groups in neurobiology have embarked into deciphering the brain circuitry using large-scale imaging of a mouse brain and manual tracing of the connections between neurons. Creating a graph of the brain circuitry, also called a connectome, could have a huge impact on the understanding of neurodegenerative diseases such as Alzheimer’s disease. Although considerably smaller than a human brain, a mouse brain already exhibits one billion connections and manually tracing the connectome of a mouse brain can only be achieved partially. This paper proposes to scale up the tracing by using automated image segmentation and a parallel computing approach designed for domain experts. We explain the design decisions behind our parallel approach and we present our results for the segmentation of the vasculature and the cell nuclei, which have been obtained without any manual intervention.