Dipy, a library for the analysis of diffusion MRI data
Open accessAbstract
Diffusion Imaging in Python (Dipy) is a free and open source software project for the analysis of data from diffusion magnetic resonance imaging (dMRI) experiments. dMRI is an application of MRI that can be used to measure structural features of brain white matter. Many methods have been developed to use dMRI data to model the local configuration of white matter nerve fiber bundles and infer the trajectory of bundles connecting different parts of the brain. Dipy gathers implementations of many different methods in dMRI, including: diffusion signal pre-processing; reconstruction of diffusion distributions in individual voxels; fiber tractography and fiber track post-processing, analysis and visualization. Dipy aims to provide transparent implementations for all the different steps of dMRI analysis with a uniform programming interface. We have implemented classical signal reconstruction techniques, such as the diffusion tensor model and deterministic fiber tractography. In addition, cutting edge novel reconstruction techniques are implemented, such as constrained spherical deconvolution and diffusion spectrum imaging (DSI) with deconvolution, as well as methods for probabilistic tracking and original methods for tractography clustering. Many additional utility functions are provided to calculate various statistics, informative visualizations, as well as file-handling routines to assist in the development and use of novel techniques. In contrast to many other scientific software projects, Dipy is not being developed by a single research group. Rather, it is an open project that encourages contributions from any scientist/developer through GitHub and open discussions on the project mailing list. Consequently, Dipy today has an international team of contributors, spanning seven different academic institutions in five countries and three continents, which is still growing.
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The MRtrix3 Python scripting library does not provide functionality to manipulate raw image data within Python itself, but provides functionality to invoke and manage external high-performance executables to perform the actual computations.
“In contrast to projects such as DiPy (Garyfallidis et al., 2014) , this library does not provide functionality to manipulate raw image data within Python itself, but provides functionality to invoke and manage external high-performance executables to perform the actual computations.”
From MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation (2019) · cites this paper as Garyfallidis et al., 2014
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Surface-enhanced tractography (SET)
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Long-Term Abnormalities in the Corpus Callosum of Female Concussed Athletes
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Patch2Self: Denoising Diffusion MRI with Self-Supervised LearningPreprint
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Self-citationData-Driven Subtyping of Executive Function–Related Behavioral Problems in Children
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- Authors
- Garyfallidis, E., Brett, M., Amirbekian, B., Rokem, A., van der Walt, S., Descoteaux, M., Nimmo-Smith, I., & Contributors, D.
- Affiliations
- Université de Sherbrooke (CA)
- University of California, Berkeley (US)
- University of California, San Francisco (US)
- Stanford University (US)
- Corresponding author
- Garyfallidis, Eleftherios
- Venue
- Frontiers in Neuroinformatics
- Publisher
- Frontiers Media SA
- Published
- 2014-02-21
- Volume
- 8
- Pages
- 8-8
- ISSN
- 1662-5196 (ISSN-L)
- PMC
- PMC3931231
- OpenAlex
- W2062791478
- Cited by
- 1,371
- References
- 98
- Citations by year
- 2026: 147 · 2025: 192 · 2024: 177 · 2023: 162 · 2022: 151 · 2021: 147 · 2020: 100 · 2019: 89 · 2018: 54 · 2017: 79 · 2016: 34 · 2015: 26 · 2014: 12 · 2013: 1
- FWCI
- 39.38
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Frontiers in Neuroinformatics (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- University of Birmingham Research Portal (University of Birmingham) (submittedVersion, cc-by)
- Funders
- Fonds Québécois de la Recherche sur la Nature et les Technologies
- Natural Sciences and Engineering Research Council of Canada
- National Eye Institute (F32EY022294)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- diffusion MRI, DIPY, white matter, fiber tractography, diffusion tensor model, constrained spherical deconvolution, diffusion spectrum imaging, probabilistic tracking, open source software, Python library
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