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A Monte Carlo-Based Fiber Tracking Algorithm using Diffusion Tensor MRI

Diffusion tensor magnetic resonance imaging, which measures directional information of water diffusion in the brain, has emerged as a powerful tool for human brain studies. In this paper, we introduce a new Monte Carlo-based fiber tracking approach to estimate brain connectivity. One of the main characteristics of this approach is that all parameters of the algorithm are automatically determined at each point using the entropy of the eigenvalues of the diffusion tensor. Experimental results show the good performance of the proposed approach

IEEE

Autor: Prados Carrasco, Ferran
Bardera i Reig, Antoni
Sbert, Mateu
Boada, Imma
Feixas Feixas, Miquel
Resum: Diffusion tensor magnetic resonance imaging, which measures directional information of water diffusion in the brain, has emerged as a powerful tool for human brain studies. In this paper, we introduce a new Monte Carlo-based fiber tracking approach to estimate brain connectivity. One of the main characteristics of this approach is that all parameters of the algorithm are automatically determined at each point using the entropy of the eigenvalues of the diffusion tensor. Experimental results show the good performance of the proposed approach
Accés al document: http://hdl.handle.net/2072/94965
Llenguatge: eng
Editor: IEEE
Drets: Tots els drets reservats
Matèria: Cervell
Entropia
Montecarlo, Mètode de
Valors propis
Brain
Entropy
Eigenvalues
Monte Carlo method
Títol: A Monte Carlo-Based Fiber Tracking Algorithm using Diffusion Tensor MRI
Tipus: info:eu-repo/semantics/article
Repositori: Recercat

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