Cited by 157Advanced Neuroimaging Techniques and ApplicationsFunctional Brain Connectivity StudiesMedical Image Segmentation Techniques

Robust clustering of massive tractography datasets

Guevara, P., Poupon, C., Rivière, D., Cointepas, Y., Descoteaux, M., Thirion, B., Mangin, J.-F.·2011·NeuroImage

Abstract

This paper presents a clustering method that detects the fiber bundles embedded in any MR-diffusion based tractography dataset. Our method can be seen as a compressing operation, capturing the most meaningful information enclosed in the fiber dataset. For the sake of efficiency, part of the analysis is based on clustering the white matter (WM) voxels rather than the fibers. The resulting regions of interest are used to define subset of fibers that are subdivided further into consistent bundles using a clustering of the fiber extremities. The dataset is reduced from more than one million fiber tracts to about two thousand fiber bundles. Validations are provided using simulated data and a physical phantom. We see our approach as a crucial preprocessing step before further analysis of huge fiber datasets. An important application will be the inference of detailed models of the subdivisions of white matter pathways and the mapping of the main U-fiber bundles.

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Crossref · 10.1016/j.neuroimage.2010.10.028

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47 of 47 references verified0 citation errors · 0 not checkable

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  • The principle of inferring connectivity from local orientation fields can lead to problems as soon as pathways overlap, cross, branch, and have complex geometries.

    “Conceptually, the principle of inferring connectivity from local orientation fields can lead to problems as soon as pathways overlap, cross, branch, and have complex geometries7, 35, 36.”
  • Regions of white matter bottlenecks have been discussed in the past and highlighted as critical with respect to tractographic findings.

    “Regions of white matter bottlenecks have been discussed in the past35 and have been highlighted as critical with respect to tractographic findings36.”

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Authors
Guevara, P., Poupon, C., Rivière, D., Cointepas, Y., Descoteaux, M., Thirion, B., & Mangin, J.-F.
Affiliations
  • University of Concepción (CL)
  • Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR)
  • Université de Sherbrooke (CA)
  • Institut national de recherche en sciences et technologies du numérique (FR)
Corresponding author
Guevara, P.
Venue
NeuroImage
Publisher
Elsevier BV
Published
2011-02
Volume
54
Issue
3
Pages
1975-1993
ISSN
1053-8119 (ISSN-L)
OpenAlex
W1966699768
Cited by
157
References
47
Citations by year
2026: 3 · 2025: 6 · 2024: 7 · 2023: 8 · 2022: 9 · 2021: 8 · 2020: 16 · 2019: 8 · 2018: 8 · 2017: 11 · 2016: 15 · 2015: 15 · 2014: 17 · 2013: 13 · 2012: 5
FWCI
6.50
Type
journal article
Language
en
Open access
closed
Locations
  • NeuroImage (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • Région Ile-de-France (France)
  • French Embassy in Chile
  • CONICYT Chile
  • University of Concepción (Chile)
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
Keywords
diffusion MRI tractography
MeSH terms
Adult, Algorithms, Brain, Child, Computer Simulation, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Nerve Fibers, Neural Pathways, Reproducibility of Results, Cluster Analysis, Databases, Factual, Phantoms, Imaging, Data Compression, Diffusion Tensor Imaging

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