Your browser doesn't support javascript.
loading
Mapping Structural Connectivity Using Diffusion MRI: Challenges and Opportunities.
Yeh, Chun-Hung; Jones, Derek K; Liang, Xiaoyun; Descoteaux, Maxime; Connelly, Alan.
Afiliação
  • Yeh CH; Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital, Taoyuan, Taiwan.
  • Jones DK; Department of Child and Adolescent Psychiatry, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan, Taiwan.
  • Liang X; Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia.
  • Descoteaux M; Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia.
  • Connelly A; Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK.
J Magn Reson Imaging ; 53(6): 1666-1682, 2021 06.
Article em En | MEDLINE | ID: mdl-32557893
ABSTRACT
Diffusion MRI-based tractography is the most commonly-used technique when inferring the structural brain connectome, i.e., the comprehensive map of the connections in the brain. The utility of graph theory-a powerful mathematical approach for modeling complex network systems-for analyzing tractography-based connectomes brings important opportunities to interrogate connectome data, providing novel insights into the connectivity patterns and topological characteristics of brain structural networks. When applying this framework, however, there are challenges, particularly regarding methodological and biological plausibility. This article describes the challenges surrounding quantitative tractography and potential solutions. In addition, challenges related to the calculation of global network metrics based on graph theory are discussed.Evidence Level 5Technical Efficacy Stage 1.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Conectoma Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Conectoma Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article