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Automatic Tracing of Ultra-Volume of Neuronal Images

By Hanchuan Peng, Zhi Zhou, Erik Meijering, Ting Zhao, Giorgio A Ascoli, Michael Hawrylycz

Posted 14 Nov 2016
bioRxiv DOI: 10.1101/087726 (published DOI: 10.1038/nmeth.4233)

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.

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