A Hough Transform Global Probabilistic Approach to Multiple-Subject Diffusion MRI Tractography
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 a 1.5T physical phantom to 7T and 4T human brain and 7T monkey brain datasets.
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 01, 2010
- Accession Number
- ADA540720
Entities
People
- Christophe Lenglet
- Essa Yacoub
- Guillermo Sapiro
- Iman Aganj
- Neda Jahanshad
- Noam Harel
- Paul M. Thompson
Organizations
- University of Minnesota