Mindboggling morphometry of human brains
Name
Klein-2017-Mindboggling morphometry of human b.pdf
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8.88 MB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Klein, Arno
Bao, Forrest S.
Giard, Joachim
Stavsky, Eliezer
Lee, Noah
Rossa, Brian
Reuter, Martin
Chaibub Neto, Elias
Keshavan, Anisha
Hame, Yrjo
Date Issued
February 2017
Journal
PLOS Computational Biology
Publisher
Public Library of Science
Citation
Klein, Arno; Ghosh, Satrajit S.; Bao, Forrest S.; Giard, Joachim; H?me, Yrj?; Stavsky, Eliezer; Lee, Noah et al. “Mindboggling Morphometry of Human Brains.” Edited by Dina Schneidman. PLOS Computational Biology 13, no. 2 (February 2017): e1005350 © 2017 Klein et al
Version
Final published version
Abstract
Mindboggle (http://mindboggle.info) is an open source brain morphometry platform that takes in preprocessed T1-weighted MRI data and outputs volume, surface, and tabular data containing label, feature, and shape information for further analysis. In this article, we document the software and demonstrate its use in studies of shape variation in healthy and diseased humans. The number of different shape measures and the size of the populations make this the largest and most detailed shape analysis of human brains ever conducted. Brain image morphometry shows great potential for providing much-needed biological markers for diagnosing, tracking, and predicting progression of mental health disorders. Very few software algorithms provide more than measures of volume and cortical thickness, while more subtle shape measures may provide more sensitive and specific biomarkers. Mindboggle computes a variety of (primarily surface-based) shapes: area, volume, thickness, curvature, depth, Laplace-Beltrami spectra, Zernike moments, etc. We evaluate Mindboggle’s algorithms using the largest set of manually labeled, publicly available brain images in the world and compare them against state-of-the-art algorithms where they exist. All data, code, and results of these evaluations are publicly available.
MIT Department
McGovern Institute for Brain Research at MIT
Terms of Use
Creative Commons Attribution 4.0 International License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1371/journal.pcbi.1005350
