Abstract:
While diffusion tensor imaging (DTI) provides a powerful tool to reconstruct neural pathways in vivo, the standard diffusion tensor model is limited to resolve a single f...Show MoreMetadata
Abstract:
While diffusion tensor imaging (DTI) provides a powerful tool to reconstruct neural pathways in vivo, the standard diffusion tensor model is limited to resolve a single fiber direction within each voxel. To overcome this difficulty, high angular resolution diffusion imaging (HARDI) has recently been proposed to investigate intravoxel fiber heterogeneity. In this paper we propose a novel method for mixture model decomposition of the HARDI signal based on Bayesian inference and trans-dimensional Markov Chain simulation. The method is applied to both synthetic and real data.
Published in: 2005 13th European Signal Processing Conference
Date of Conference: 04-08 September 2005
Date Added to IEEE Xplore: 06 April 2015
Print ISBN:978-160-4238-21-1
Conference Location: Antalya, Turkey