RT Journal Article
SR Electronic
T1 Automatic Tracing of Ultra-Volume of Neuronal Images
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 087726
DO 10.1101/087726
A1 Hanchuan Peng
A1 Zhi Zhou
A1 Erik Meijering
A1 Ting Zhao
A1 Giorgio A. Ascoli
A1 Michael Hawrylycz
YR 2016
UL http://biorxiv.org/content/early/2016/11/14/087726.abstract
AB Despite substantial advancement in the automatic tracing of neurons' morphology in recent years, it is challenging to apply the existing algorithms to very large image datasets containing billions or more voxels. We introduce UltraTracer, a solution designed to extend any base neuron-tracing algorithm to be able to trace virtually unlimited data volumes. We applied this approach to neuron-tracing algorithms with completely different design principles and tested on challenging human and mouse neuron datasets that have hundreds of billions of voxels. Results indicate that UltraTracer is scalable, accurate, and about 3 to 6 times more efficient compared to other state-of-the-art approaches.