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Neuroinformatics

, Volume 15, Issue 1, pp 71–86 | Cite as

Fast Automatic Segmentation of White Matter Streamlines Based on a Multi-Subject Bundle Atlas

  • Nicole LabraEmail author
  • Pamela GuevaraEmail author
  • Delphine Duclap
  • Josselin Houenou
  • Cyril Poupon
  • Jean-François Mangin
  • Miguel FigueroaEmail author
Original Article

Abstract

This paper presents an algorithm for fast segmentation of white matter bundles from massive dMRI tractography datasets using a multisubject atlas. We use a distance metric to compare streamlines in a subject dataset to labeled centroids in the atlas, and label them using a per-bundle configurable threshold. In order to reduce segmentation time, the algorithm first preprocesses the data using a simplified distance metric to rapidly discard candidate streamlines in multiple stages, while guaranteeing that no false negatives are produced. The smaller set of remaining streamlines is then segmented using the original metric, thus eliminating any false positives from the preprocessing stage. As a result, a single-thread implementation of the algorithm can segment a dataset of almost 9 million streamlines in less than 6 minutes. Moreover, parallel versions of our algorithm for multicore processors and graphics processing units further reduce the segmentation time to less than 22 seconds and to 5 seconds, respectively. This performance enables the use of the algorithm in truly interactive applications for visualization, analysis, and segmentation of large white matter tractography datasets.

Keywords

Diffusion-weighted MRI HARDI data White matter tracts Tractography segmentation Streamline distance GPU programming 

Notes

Acknowledgments

This work was partially funded by FONDECYT grants 1151278 and 11121644, and PIA-CONICYT PFB0824. Thanks to Marion Leboyer for providing a testing HARDI database.

The “CONNECT/ARCHI Database” is the property of the CEA I2BM NeuroSpin centre and was designed under the supervision of Dr Cyril Poupon and Dr Jean-François Mangin, and was funded by the Federative Research Institute 49, by the HIPPIP European grant, and the European CONNECT project (http://www.brain-connect.eu). Acquisitions were performed by the scientists involved in the Multi-scale Brain Architecture research program of NeuroSpin and by the staff of the UNIACT Laboratory of NeuroSpin (headed by Dr. Lucie Hertz-Pannier), under the ethical approval CPP100002/CPP100022 (principal investigator Dr. Denis Le Bihan).

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Universidad de ConcepciónConcepciónChile
  2. 2.NeurospinI2BM, CEAGif-sur-YvetteFrance
  3. 3.APHP, Pôle de Psychiatrie, DHU PePsy, INSERM U955 Eq. 15 “Psychiatrie Translationnelle”Université Paris EstCréteilFrance

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