| Literature DB >> 28231282 |
Arno Klein1, Satrajit S Ghosh2,3, Forrest S Bao4, Joachim Giard5, Yrjö Häme6, Eliezer Stavsky6, Noah Lee6, Brian Rossa7, Martin Reuter8, Elias Chaibub Neto9, Anisha Keshavan10.
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.Entities:
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Year: 2017 PMID: 28231282 PMCID: PMC5322885 DOI: 10.1371/journal.pcbi.1005350
Source DB: PubMed Journal: PLoS Comput Biol ISSN: 1553-734X Impact factor: 4.475