A hitchhiker's guide to diffusion tensor imaging

Detalhes bibliográficos
Autor(a) principal: Soares, José Miguel
Data de Publicação: 2013
Outros Autores: Alves, Victor, Sousa, Nuno, Marques, Paulo César Gonçalves
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/1822/24202
Resumo: Diffusion Tensor Imaging (DTI) studies are increasingly popular among clinicians and researchers as they provide unique insights into brain network connectivity. However, in order to optimize the use of DTI, several technical and methodological aspects must be factored in. These include decisions on: acquisition protocol, artifact handling, data quality control, reconstruction algorithm, and visualization approaches, and quantitative analysis methodology. Furthermore, the researcher and/or clinician also needs to take into account and decide on the most suited software tool(s) for each stage of the DTI analysis pipeline. Herein, we provide a straightforward hitchhiker's guide, covering all of the workflow's major stages. Ultimately, this guide will help newcomers navigate the most critical roadblocks in the analysis and further encourage the use of DTI.
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spelling A hitchhiker's guide to diffusion tensor imagingDiffusion tensor imagingHitchhiker's guideAcquisitionAnalysisProcessingScience & TechnologyDiffusion Tensor Imaging (DTI) studies are increasingly popular among clinicians and researchers as they provide unique insights into brain network connectivity. However, in order to optimize the use of DTI, several technical and methodological aspects must be factored in. These include decisions on: acquisition protocol, artifact handling, data quality control, reconstruction algorithm, and visualization approaches, and quantitative analysis methodology. Furthermore, the researcher and/or clinician also needs to take into account and decide on the most suited software tool(s) for each stage of the DTI analysis pipeline. Herein, we provide a straightforward hitchhiker's guide, covering all of the workflow's major stages. Ultimately, this guide will help newcomers navigate the most critical roadblocks in the analysis and further encourage the use of DTI.The work was supported by SwitchBox-FP7-HEALTH-2010-grant 259772-2. The authors acknowledge Nadine Santos for her help in editing the manuscript.Frontiers MediaUniversidade do MinhoSoares, José MiguelAlves, VictorSousa, NunoMarques, Paulo César Gonçalves2013-032013-03-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/24202eng1662-454810.3389/fnins.2013.00031http://dx.doi.org/10.3389/fnins.2013.00031info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:34:01ZPortal AgregadorONG
dc.title.none.fl_str_mv A hitchhiker's guide to diffusion tensor imaging
title A hitchhiker's guide to diffusion tensor imaging
spellingShingle A hitchhiker's guide to diffusion tensor imaging
Soares, José Miguel
Diffusion tensor imaging
Hitchhiker's guide
Acquisition
Analysis
Processing
Science & Technology
title_short A hitchhiker's guide to diffusion tensor imaging
title_full A hitchhiker's guide to diffusion tensor imaging
title_fullStr A hitchhiker's guide to diffusion tensor imaging
title_full_unstemmed A hitchhiker's guide to diffusion tensor imaging
title_sort A hitchhiker's guide to diffusion tensor imaging
author Soares, José Miguel
author_facet Soares, José Miguel
Alves, Victor
Sousa, Nuno
Marques, Paulo César Gonçalves
author_role author
author2 Alves, Victor
Sousa, Nuno
Marques, Paulo César Gonçalves
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Soares, José Miguel
Alves, Victor
Sousa, Nuno
Marques, Paulo César Gonçalves
dc.subject.por.fl_str_mv Diffusion tensor imaging
Hitchhiker's guide
Acquisition
Analysis
Processing
Science & Technology
topic Diffusion tensor imaging
Hitchhiker's guide
Acquisition
Analysis
Processing
Science & Technology
description Diffusion Tensor Imaging (DTI) studies are increasingly popular among clinicians and researchers as they provide unique insights into brain network connectivity. However, in order to optimize the use of DTI, several technical and methodological aspects must be factored in. These include decisions on: acquisition protocol, artifact handling, data quality control, reconstruction algorithm, and visualization approaches, and quantitative analysis methodology. Furthermore, the researcher and/or clinician also needs to take into account and decide on the most suited software tool(s) for each stage of the DTI analysis pipeline. Herein, we provide a straightforward hitchhiker's guide, covering all of the workflow's major stages. Ultimately, this guide will help newcomers navigate the most critical roadblocks in the analysis and further encourage the use of DTI.
publishDate 2013
dc.date.none.fl_str_mv 2013-03
2013-03-01T00:00:00Z
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/24202
url http://hdl.handle.net/1822/24202
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1662-4548
10.3389/fnins.2013.00031
http://dx.doi.org/10.3389/fnins.2013.00031
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dc.publisher.none.fl_str_mv Frontiers Media
publisher.none.fl_str_mv Frontiers Media
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