Tractography analysis with the scilpy toolbox

2026/01/08 by Emmanuelle Renauld, Arnaud Boré, Charles Poirier +22 · 1 voice · 3 citations
Medicine · Neuroscience · #Advanced Neuroimaging Techniques and Applications #Functional Brain Connectivity Studies #Fetal and Pediatric Neurological Disorders

paper · pdf · doi:10.52294/001c.154022

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.

Cited by

• Mapping heterogeneous region- and tissue-specific brain ageing patterns using quantitative MRI. [europepmc]
• Cross-site quantitative MRI harmonization: The impact on age modeling in health and disease. [europepmc]
• Bridging Histology and Tractography: First In Vivo Visualization of Short-Range Prefrontal Connections Informed by Primate Tract-Tracing. [europepmc]

Discussions

• Renauld et al. present scilpy, an open-source #Python library for diffusion magnetic resonance imaging and tractography: doi.org/10.52294/001... @ohbmofficial.bsky.social [bsky, 25 points, 0 comments]

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