Tractography analysis with the scilpy toolbox

We present scilpy, an open-source Python library for diffusion magnetic resonance imaging (dMRI) and tractography. It provides a large collection of well-documented, user-friendly scripts that support nearly every stage of the dMRI processing pipeline, from preprocessing (such as denoising, registration, and local fiber reconstruction) to tractography and post-processing of tractograms, including connectivity and bundle analyses. Scilpy leverages the strength of DIPY, is well-tested through modern continuous integration practices, and is actively maintained.

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Publication Details

Journal
Aperture Neuro
Published
2026-01-08
DOI
https://doi.org/10.52294/001c.154022
Citations
2
Primary Topic
Advanced Neuroimaging Techniques and Applications
Type
article
Field-Weighted Citation Impact
63.85
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article

Tractography analysis with the scilpy toolbox

Gabrielle Grenier, Emmanuelle Renauld, Graham Little, Etienne St‐Onge et al.
2 citations
Aperture Neuro
Advanced Neuroimaging Techniques and Applications
63.85
article

Tractography analysis with the scilpy toolbox

Gabrielle Grenier, Emmanuelle Renauld, Graham Little, Etienne St‐Onge, Philippe Poulin, Vincent Beaudoin, Arnaud Boré, Charles Poirier, Guillaume Theaud, Philippe Karan, Antoine Théberge, Maxime Descôteaux, Anthony Gagnon, Mario Ocampo Pineda, Laurent Petit, François Rheault, Manon Edde, Alexandre Joanisse, Jean-Christophe Houde, Matteo Battochio, Stanislas Thoumyre, Zineb El Yamani, Gabriel Girard, Jon Haitz Legarreta, Alex Valcourt-Caron
article en
2 citations

Abstract

We present scilpy, an open-source Python library for diffusion magnetic resonance imaging (dMRI) and tractography. It provides a large collection of well-documented, user-friendly scripts that support nearly every stage of the dMRI processing pipeline, from preprocessing (such as denoising, registration, and local fiber reconstruction) to tractography and post-processing of tractograms, including connectivity and bundle analyses. Scilpy leverages the strength of DIPY, is well-tested through modern continuous integration practices, and is actively maintained.

Aperture NeuroVol. 6
University of Verona (IT), Brigham and Women's Hospital (US), Centre National de la Recherche Scientifique (FR), Université de Sherbrooke (CA), Harvard University (US), Université de Bordeaux (FR), University of Basel (CH), Université du Québec en Outaouais (CA), Centre Émile Durkheim (FR), Université de Montréal (CA)
Openalex Percentile: Top 0%
Advanced Neuroimaging Techniques and Applications
63.85
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