Display Settings:

Format

Send to:

Choose Destination
See comment in PubMed Commons below
Med Image Anal. 2011 Aug;15(4):414-25. doi: 10.1016/j.media.2011.01.003. Epub 2011 Jan 26.

A Hough transform global probabilistic approach to multiple-subject diffusion MRI tractography.

Author information

  • 1Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, 200 Union St. SE, MN 55455, USA. iman@umn.edu

Abstract

A global probabilistic fiber tracking approach based on the voting process provided by the Hough transform is introduced in this work. The proposed framework tests candidate 3D curves in the volume, assigning to each one a score computed from the diffusion images, and then selects the curves with the highest scores as the potential anatomical connections. The algorithm avoids local minima by performing an exhaustive search at the desired resolution. The technique is easily extended to multiple subjects, considering a single representative volume where the registered high-angular resolution diffusion images (HARDI) from all the subjects are non-linearly combined, thereby obtaining population-representative tracts. The tractography algorithm is run only once for the multiple subjects, and no tract alignment is necessary. We present experimental results on HARDI volumes, ranging from simulated and 1.5T physical phantoms to 7T and 4T human brain and 7T monkey brain datasets.

Copyright © 2011 Elsevier B.V. All rights reserved.

PMID:
21376655
[PubMed - indexed for MEDLINE]
PMCID:
PMC3115463
Free PMC Article

Images from this publication.See all images (10)Free text

Fig 1
Fig 2
Fig 3
Fig 4
Fig 5
Fig 6
Fig 7
Fig 8
Fig 9
Fig 10

Publication Types, MeSH Terms, Grant Support

Publication Types

MeSH Terms

Grant Support

PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Icon for Elsevier Science Icon for PubMed Central
    Loading ...
    Write to the Help Desk