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.
Publication types
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Research Support, Non-U.S. Gov't
MeSH terms
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Algorithms
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Brain / physiology
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Brain Mapping / methods
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Computer Graphics
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Computers
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Connectome*
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Data Interpretation, Statistical
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Diffusion Magnetic Resonance Imaging / methods
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Humans
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Image Processing, Computer-Assisted / methods*
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Internet
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Magnetic Resonance Imaging / methods*
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Models, Statistical
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Programming Languages
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Software
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User-Computer Interface
Grants and funding
This project was partially supported by Swiss National Science Foundation (grant N°320030-130090) and SPUM (grants N°33CM30-124089 and 320030-141165), as well as the Centre d'Imagerie BioMédicale (CIBM) of the Geneva-Lausanne universities and the Swiss Federal Institute of Technology Lausanne (EPFL), the Leenaards and Louis-Jeantet foundations. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.