A browser-based tool for visualization and analysis of diffusion MRI data

Jason D. Yeatman; Adam Richie-Halford; Josh K. Smith; Anisha Keshavan; Ariel Rokem

doi:10.1038/s41467-018-03297-7

Nature Communications (Mar 2018)

A browser-based tool for visualization and analysis of diffusion MRI data

Jason D. Yeatman,
Adam Richie-Halford,
Josh K. Smith,
Anisha Keshavan,
Ariel Rokem

Affiliations

Jason D. Yeatman: Institute for Learning & Brain Sciences, University of Washington
Adam Richie-Halford: Department of Physics, University of Washington
Josh K. Smith: Department of Chemical Engineering, University of Washington
Anisha Keshavan: Institute for Learning & Brain Sciences, University of Washington
Ariel Rokem: eScience Institute, WRF Data Science Studio, University of Washington

DOI: https://doi.org/10.1038/s41467-018-03297-7
Journal volume & issue: Vol. 9, no. 1
pp. 1 – 10

Abstract

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Data sharing is an important component of reproducible research, but meaningful data sharing can be difficult. Here authors describe a new open source tool, AFQ-Browser, that builds an interactive website allowing visualization and exploratory data analysis of published diffusion MRI data.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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