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TeraVR empowers precise reconstruction of complete 3-D neuronal morphology in the whole brain

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Title: TeraVR empowers precise reconstruction of complete 3-D neuronal morphology in the whole brain
Authors: Wang, Y
Li, Q
Liu, L
Zhou, Z
Ruan, Z
Kong, L
Li, Y
Wang, Y
Zhong, N
Chai, R
Luo, X
Guo, Y
Hawrylycz, M
Luo, Q
Gu, Z
Xie, W
Zeng, H
Peng, H
Item Type: Journal Article
Abstract: Neuron morphology is recognized as a key determinant of cell type, yet the quantitative profiling of a mammalian neuron's complete three-dimensional (3-D) morphology remains arduous when the neuron has complex arborization and long projection. Whole-brain reconstruction of neuron morphology is even more challenging as it involves processing tens of teravoxels of imaging data. Validating such reconstructions is extremely laborious. We develop TeraVR, an open-source virtual reality annotation system, to address these challenges. TeraVR integrates immersive and collaborative 3-D visualization, interaction, and hierarchical streaming of teravoxel-scale images. Using TeraVR, we have produced precise 3-D full morphology of long-projecting neurons in whole mouse brains and developed a collaborative workflow for highly accurate neuronal reconstruction.
Issue Date: 2-Aug-2019
Date of Acceptance: 16-Jul-2019
URI: http://hdl.handle.net/10044/1/72382
DOI: https://dx.doi.org/10.1038/s41467-019-11443-y
ISSN: 2041-1723
Publisher: Nature Research (part of Springer Nature)
Journal / Book Title: Nature Communications
Volume: 10
Issue: 1
Copyright Statement: © The Author(s) 2019. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Keywords: MD Multidisciplinary
Publication Status: Published
Conference Place: England
Article Number: ARTN 3474
Online Publication Date: 2019-08-02
Appears in Collections:Computing