A Hough Transform Global Probabilistic Approach to Multiple-Subject Diffusion MRI Tractography
Author
Lenglet, Christophe
Jahanshad, Neda
Yacoub, Essa
Harel, Noam
Thompson, Paul M.
Sapiro, Guillermo
Published Version
https://doi.org/10.1016/j.media.2011.01.003Metadata
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Aganj, Iman, Christophe Lenglet, Neda Jahanshad, Essa Yacoub, Noam Harel, Paul M. Thompson, Guillermo Sapiro. "A Hough Transform Global Probabilistic Approach to Multiple-Subject Diffusion MRI Tractography." Medical Image Analysis 15, no. 4 (2011): 414-425. DOI: 10.1016/j.media.2011.01.003Abstract
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.Other Sources
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3115463/Terms of Use
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