Exploring the connectome: petascale volume visualization of microscopy data streams.

Citation data:

IEEE computer graphics and applications, ISSN: 1558-1756, Vol: 33, Issue: 4, Page: 50-61

Publication Year:
2013
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Citations 16
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Repository URL:
http://hdl.handle.net/10754/562851; http://scholarworks.unist.ac.kr/handle/201301/4255
PMID:
24808059
DOI:
10.1109/mcg.2013.55
PMCID:
PMC4296712
Author(s):
Beyer, Johanna; Hadwiger, Markus; Al-Awami, Ali K.; Jeong, Wonki; Kasthuri, Narayanan; Lichtman, Jeff W M D; Pfister, Hanspeter
Publisher(s):
Institute of Electrical and Electronics Engineers (IEEE); Institute of Electrical and Electronics Engineers; IEEE COMPUTER SOC
Tags:
Computer Science; computer graphics; high-resolution microscopy; high-throughput imaging; neuroscience; petascale-volume exploration; segmented volume data; High-resolution microscopy; High-Throughput Imaging; Interactive exploration; Interactive rates; Neural structures; Volume data; Volume visualization
article description
Recent advances in high-resolution microscopy let neuroscientists acquire neural-tissue volume data of extremely large sizes. However, the tremendous resolution and the high complexity of neural structures present big challenges to storage, processing, and visualization at interactive rates. A proposed system provides interactive exploration of petascale (petavoxel) volumes resulting from high-throughput electron microscopy data streams. The system can concurrently handle multiple volumes and can support the simultaneous visualization of high-resolution voxel segmentation data. Its visualization-driven design restricts most computations to a small subset of the data. It employs a multiresolution virtual-memory architecture for better scalability than previous approaches and for handling incomplete data. Researchers have employed it for a 1-teravoxel mouse cortex volume, of which several hundred axons and dendrites as well as synapses have been segmented and labeled.