title: A CONTINUOUS MIXTURE OF TENSORS MODEL FOR DIFFUSION-WEIGHTED MR SIGNAL RECONSTRUCTION.
abstract: Diffusion MRI is a non-invasive imaging technique that allows the measurement of water molecular diffusion through tissue in vivo. In this paper, we present a novel statistical model which describes the diffusion-attenuated MR signal by the Laplace transform of a probability distribution over symmetric positive definite matrices. Using this new model, we analytically derive a Rigaut-type asymptotic fractal law for the MR signal decay which has been phenomenologically used before. We also develop an efficient scheme for reconstructing the multiple fiber bundles from the DW-MRI measurements. Experimental results on both synthetic and real data sets are presented to show the robustness and accuracy of the proposed algorithms.
authors: Department of Computer and Information Science and Engineering.
authors: Bing
authors: B
authors: Jian
authors: Baba C
authors: BC
authors: Vemuri
authors: Evren
authors: E
authors: Ozarslan
authors: Paul
authors: P
authors: Carney
authors: Thomas
authors: T
authors: Mareci