Graphical interface for automated management of motion artifact within fMRI acquisitions: INFOBAR

Independent Component Analysis-based Automatic Removal of Motion Artifacts (ICA-AROMA; Pruim et al., 2015) is a robust approach to remove brain activity related to head motion within functional magnetic resonance imaging (fMRI) datasets. However, ICA-AROMA requires command line implementation and cu...

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Autores principales: Anand, Manish, Diekfuss, Jed A., Slutsky-Ganesh, Alexis B., Bonnette, Scott, Grooms, Dustin R., Myer, Gregory D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7806167/
https://www.ncbi.nlm.nih.gov/pubmed/33447655
http://dx.doi.org/10.1016/j.softx.2020.100598
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author Anand, Manish
Diekfuss, Jed A.
Slutsky-Ganesh, Alexis B.
Bonnette, Scott
Grooms, Dustin R.
Myer, Gregory D.
author_facet Anand, Manish
Diekfuss, Jed A.
Slutsky-Ganesh, Alexis B.
Bonnette, Scott
Grooms, Dustin R.
Myer, Gregory D.
author_sort Anand, Manish
collection PubMed
description Independent Component Analysis-based Automatic Removal of Motion Artifacts (ICA-AROMA; Pruim et al., 2015) is a robust approach to remove brain activity related to head motion within functional magnetic resonance imaging (fMRI) datasets. However, ICA-AROMA requires command line implementation and customized code to batch process large datasets. We developed a cross-platform, open-source graphical user Interface for Batch processing fMRI datasets using ICA-AROMA (INFOBAR). INFOBAR allows a user to search directories, identify appropriate datasets, and batch execute ICA-AROMA. INFOBAR also has additional data processing options and visualization features to support all researchers interested in mitigating head motion artifact in post-processing using ICA-AROMA.
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spelling pubmed-78061672021-01-13 Graphical interface for automated management of motion artifact within fMRI acquisitions: INFOBAR Anand, Manish Diekfuss, Jed A. Slutsky-Ganesh, Alexis B. Bonnette, Scott Grooms, Dustin R. Myer, Gregory D. SoftwareX Article Independent Component Analysis-based Automatic Removal of Motion Artifacts (ICA-AROMA; Pruim et al., 2015) is a robust approach to remove brain activity related to head motion within functional magnetic resonance imaging (fMRI) datasets. However, ICA-AROMA requires command line implementation and customized code to batch process large datasets. We developed a cross-platform, open-source graphical user Interface for Batch processing fMRI datasets using ICA-AROMA (INFOBAR). INFOBAR allows a user to search directories, identify appropriate datasets, and batch execute ICA-AROMA. INFOBAR also has additional data processing options and visualization features to support all researchers interested in mitigating head motion artifact in post-processing using ICA-AROMA. 2020-10-21 2020 /pmc/articles/PMC7806167/ /pubmed/33447655 http://dx.doi.org/10.1016/j.softx.2020.100598 Text en http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license.
spellingShingle Article
Anand, Manish
Diekfuss, Jed A.
Slutsky-Ganesh, Alexis B.
Bonnette, Scott
Grooms, Dustin R.
Myer, Gregory D.
Graphical interface for automated management of motion artifact within fMRI acquisitions: INFOBAR
title Graphical interface for automated management of motion artifact within fMRI acquisitions: INFOBAR
title_full Graphical interface for automated management of motion artifact within fMRI acquisitions: INFOBAR
title_fullStr Graphical interface for automated management of motion artifact within fMRI acquisitions: INFOBAR
title_full_unstemmed Graphical interface for automated management of motion artifact within fMRI acquisitions: INFOBAR
title_short Graphical interface for automated management of motion artifact within fMRI acquisitions: INFOBAR
title_sort graphical interface for automated management of motion artifact within fmri acquisitions: infobar
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7806167/
https://www.ncbi.nlm.nih.gov/pubmed/33447655
http://dx.doi.org/10.1016/j.softx.2020.100598
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