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BMAT: An open-source BIDS managing and analysis tool

Magnetic Resonance Imaging (MRI) is an established technique to study in vivo neurological disorders such as Multiple Sclerosis (MS). To avoid errors on MRI data organization and automated processing, a standard called Brain Imaging Data Structure (BIDS) has been recently proposed. The BIDS standard...

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Autores principales: Vanden Bulcke, Colin, Wynen, Maxence, Detobel, Jules, La Rosa, Francesco, Absinta, Martina, Dricot, Laurence, Macq, Benoît, Bach Cuadra, Meritxell, Maggi, Pietro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9723304/
https://www.ncbi.nlm.nih.gov/pubmed/36451357
http://dx.doi.org/10.1016/j.nicl.2022.103252
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author Vanden Bulcke, Colin
Wynen, Maxence
Detobel, Jules
La Rosa, Francesco
Absinta, Martina
Dricot, Laurence
Macq, Benoît
Bach Cuadra, Meritxell
Maggi, Pietro
author_facet Vanden Bulcke, Colin
Wynen, Maxence
Detobel, Jules
La Rosa, Francesco
Absinta, Martina
Dricot, Laurence
Macq, Benoît
Bach Cuadra, Meritxell
Maggi, Pietro
author_sort Vanden Bulcke, Colin
collection PubMed
description Magnetic Resonance Imaging (MRI) is an established technique to study in vivo neurological disorders such as Multiple Sclerosis (MS). To avoid errors on MRI data organization and automated processing, a standard called Brain Imaging Data Structure (BIDS) has been recently proposed. The BIDS standard eases data sharing and processing within or between centers by providing guidelines for their description and organization. However, the transformation from the complex unstructured non-open file data formats coming directly from the MRI scanner to a correct BIDS structure can be cumbersome and time consuming. This hinders a wider adoption of the BIDS format across different study centers. To solve this problem and ease the day-to-day use of BIDS for the neuroimaging scientific community, we present the BIDS Managing and Analysis Tool (BMAT). The BMAT software is a complete and easy-to-use local open-source neuroimaging analysis tool with a graphical user interface (GUI) that uses the BIDS format to organize and process brain MRI data for MS imaging research studies. BMAT provides the possibility to translate data from MRI scanners to the BIDS structure, create and manage BIDS datasets as well as develop and run automated processing pipelines, and is faster than its competitor. BMAT software propose the possibility to download useful analysis apps, especially applied to MS research with lesion segmentation and processing of imaging contrasts for novel disease biomarkers such as the central vein sign and the paramagnetic rim lesions.
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spelling pubmed-97233042022-12-07 BMAT: An open-source BIDS managing and analysis tool Vanden Bulcke, Colin Wynen, Maxence Detobel, Jules La Rosa, Francesco Absinta, Martina Dricot, Laurence Macq, Benoît Bach Cuadra, Meritxell Maggi, Pietro Neuroimage Clin Articles from the Special Issue on "Mapping Multiple Sclerosis: new frontiers - old challenges" Edited by Hartwig Siebner, Vanessa Wiggermann, Martina Absinta, Mark Mühlau, Oh Jiwon and Maria A. Rocca Magnetic Resonance Imaging (MRI) is an established technique to study in vivo neurological disorders such as Multiple Sclerosis (MS). To avoid errors on MRI data organization and automated processing, a standard called Brain Imaging Data Structure (BIDS) has been recently proposed. The BIDS standard eases data sharing and processing within or between centers by providing guidelines for their description and organization. However, the transformation from the complex unstructured non-open file data formats coming directly from the MRI scanner to a correct BIDS structure can be cumbersome and time consuming. This hinders a wider adoption of the BIDS format across different study centers. To solve this problem and ease the day-to-day use of BIDS for the neuroimaging scientific community, we present the BIDS Managing and Analysis Tool (BMAT). The BMAT software is a complete and easy-to-use local open-source neuroimaging analysis tool with a graphical user interface (GUI) that uses the BIDS format to organize and process brain MRI data for MS imaging research studies. BMAT provides the possibility to translate data from MRI scanners to the BIDS structure, create and manage BIDS datasets as well as develop and run automated processing pipelines, and is faster than its competitor. BMAT software propose the possibility to download useful analysis apps, especially applied to MS research with lesion segmentation and processing of imaging contrasts for novel disease biomarkers such as the central vein sign and the paramagnetic rim lesions. Elsevier 2022-11-04 /pmc/articles/PMC9723304/ /pubmed/36451357 http://dx.doi.org/10.1016/j.nicl.2022.103252 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Articles from the Special Issue on "Mapping Multiple Sclerosis: new frontiers - old challenges" Edited by Hartwig Siebner, Vanessa Wiggermann, Martina Absinta, Mark Mühlau, Oh Jiwon and Maria A. Rocca
Vanden Bulcke, Colin
Wynen, Maxence
Detobel, Jules
La Rosa, Francesco
Absinta, Martina
Dricot, Laurence
Macq, Benoît
Bach Cuadra, Meritxell
Maggi, Pietro
BMAT: An open-source BIDS managing and analysis tool
title BMAT: An open-source BIDS managing and analysis tool
title_full BMAT: An open-source BIDS managing and analysis tool
title_fullStr BMAT: An open-source BIDS managing and analysis tool
title_full_unstemmed BMAT: An open-source BIDS managing and analysis tool
title_short BMAT: An open-source BIDS managing and analysis tool
title_sort bmat: an open-source bids managing and analysis tool
topic Articles from the Special Issue on "Mapping Multiple Sclerosis: new frontiers - old challenges" Edited by Hartwig Siebner, Vanessa Wiggermann, Martina Absinta, Mark Mühlau, Oh Jiwon and Maria A. Rocca
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9723304/
https://www.ncbi.nlm.nih.gov/pubmed/36451357
http://dx.doi.org/10.1016/j.nicl.2022.103252
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