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Mindboggling morphometry of human brains.
Klein, Arno; Ghosh, Satrajit S; Bao, Forrest S; Giard, Joachim; Häme, Yrjö; Stavsky, Eliezer; Lee, Noah; Rossa, Brian; Reuter, Martin; Chaibub Neto, Elias; Keshavan, Anisha.
Afiliação
  • Klein A; Child Mind Institute, New York, New York, United States of America.
  • Ghosh SS; McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
  • Bao FS; Department of Otolaryngology, Harvard Medical School, Boston, Massachusetts, United States of America.
  • Giard J; Department of Electrical and Computer Engineering, University of Akron, Akron, Ohio, United States of America.
  • Häme Y; University of Louvain, Louvain, Belgium.
  • Stavsky E; Columbia University, New York, New York, United States of America.
  • Lee N; Columbia University, New York, New York, United States of America.
  • Rossa B; Columbia University, New York, New York, United States of America.
  • Reuter M; TankThink Labs, Boston, Massachusetts, United States of America.
  • Chaibub Neto E; Harvard Medical School, Cambridge, Massachusetts, United States of America.
  • Keshavan A; Sage Bionetworks, Seattle, Washington, United States of America.
PLoS Comput Biol ; 13(2): e1005350, 2017 02.
Article em En | MEDLINE | ID: mdl-28231282
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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Encéfalo / Encefalopatias / Pontos de Referência Anatômicos Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Female / Humans / Male Idioma: En Revista: PLoS Comput Biol Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Encéfalo / Encefalopatias / Pontos de Referência Anatômicos Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Female / Humans / Male Idioma: En Revista: PLoS Comput Biol Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Estados Unidos