The Connectome Mapper: An Open-Source Processing Pipeline to Map Connectomes with MRI
Researchers working in the field of global connectivity analysis using diffusion magnetic resonance imaging (MRI) can count on a wide selection of software packages for processing their data, with methods ranging from the reconstruction of the local intra-voxel axonal structure to the estimation of...
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| Published in | PloS one Vol. 7; no. 12; p. e48121 |
|---|---|
| Main Authors | , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Public Library of Science
18.12.2012
Public Library of Science (PLoS) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1932-6203 1932-6203 |
| DOI | 10.1371/journal.pone.0048121 |
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| Abstract | Researchers working in the field of global connectivity analysis using diffusion magnetic resonance imaging (MRI) can count on a wide selection of software packages for processing their data, with methods ranging from the reconstruction of the local intra-voxel axonal structure to the estimation of the trajectories of the underlying fibre tracts. However, each package is generally task-specific and uses its own conventions and file formats. In this article we present the Connectome Mapper, a software pipeline aimed at helping researchers through the tedious process of organising, processing and analysing diffusion MRI data to perform global brain connectivity analyses. Our pipeline is written in Python and is freely available as open-source at www.cmtk.org. |
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| AbstractList | Researchers working in the field of global connectivity analysis using diffusion magnetic resonance imaging (MRI) can count on a wide selection of software packages for processing their data, with methods ranging from the reconstruction of the local intra-voxel axonal structure to the estimation of the trajectories of the underlying fibre tracts. However, each package is generally task-specific and uses its own conventions and file formats. In this article we present the Connectome Mapper, a software pipeline aimed at helping researchers through the tedious process of organising, processing and analysing diffusion MRI data to perform global brain connectivity analyses. Our pipeline is written in Python and is freely available as open-source at www.cmtk.org. Researchers working in the field of global connectivity analysis using diffusion magnetic resonance imaging (MRI) can count on a wide selection of software packages for processing their data, with methods ranging from the reconstruction of the local intra-voxel axonal structure to the estimation of the trajectories of the underlying fibre tracts. However, each package is generally task-specific and uses its own conventions and file formats. In this article we present the Connectome Mapper, a software pipeline aimed at helping researchers through the tedious process of organising, processing and analysing diffusion MRI data to perform global brain connectivity analyses. Our pipeline is written in Python and is freely available as open-source at www.cmtk.org.Researchers working in the field of global connectivity analysis using diffusion magnetic resonance imaging (MRI) can count on a wide selection of software packages for processing their data, with methods ranging from the reconstruction of the local intra-voxel axonal structure to the estimation of the trajectories of the underlying fibre tracts. However, each package is generally task-specific and uses its own conventions and file formats. In this article we present the Connectome Mapper, a software pipeline aimed at helping researchers through the tedious process of organising, processing and analysing diffusion MRI data to perform global brain connectivity analyses. Our pipeline is written in Python and is freely available as open-source at www.cmtk.org. |
| Audience | Academic |
| Author | Daducci, Alessandro Gigandet, Xavier Thiran, Jean-Philippe Cammoun, Leila Gerhard, Stephan Meuli, Reto Hagmann, Patric Griffa, Alessandra Lemkaddem, Alia |
| AuthorAffiliation | 2 Department of Radiology, Lausanne University Hospital, and University of Lausanne, Lausanne, Switzerland 1 Signal Processing Laboratory, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland UCSF, United States of America |
| AuthorAffiliation_xml | – name: 1 Signal Processing Laboratory, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland – name: 2 Department of Radiology, Lausanne University Hospital, and University of Lausanne, Lausanne, Switzerland – name: UCSF, United States of America |
| Author_xml | – sequence: 1 givenname: Alessandro surname: Daducci fullname: Daducci, Alessandro – sequence: 2 givenname: Stephan surname: Gerhard fullname: Gerhard, Stephan – sequence: 3 givenname: Alessandra surname: Griffa fullname: Griffa, Alessandra – sequence: 4 givenname: Alia surname: Lemkaddem fullname: Lemkaddem, Alia – sequence: 5 givenname: Leila surname: Cammoun fullname: Cammoun, Leila – sequence: 6 givenname: Xavier surname: Gigandet fullname: Gigandet, Xavier – sequence: 7 givenname: Reto surname: Meuli fullname: Meuli, Reto – sequence: 8 givenname: Patric surname: Hagmann fullname: Hagmann, Patric – sequence: 9 givenname: Jean-Philippe surname: Thiran fullname: Thiran, Jean-Philippe |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/23272041$$D View this record in MEDLINE/PubMed |
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| Copyright | COPYRIGHT 2012 Public Library of Science 2012 Daducci et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2012 Daducci et al 2012 Daducci et al |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Competing Interests: The authors have declared that no competing interests exist. Conceived and designed the experiments: PH LC XG AD AL JPT. Performed the experiments: SG AD AG LC. Analyzed the data: AL AG AD RM. Wrote the paper: AD AG AL JPT. |
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| Title | The Connectome Mapper: An Open-Source Processing Pipeline to Map Connectomes with MRI |
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