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 cha...
| Autores: | , , , , |
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| Formato: | artículo |
| Fecha de publicación: | 2006 |
| País: | España |
| Recursos: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10256/3056 |
| Acesso em linha: | http://hdl.handle.net/10256/3056 |
| Access Level: | acceso abierto |
| Palavra-chave: | Cervell Entropia Montecarlo, Mètode de Valors propis Brain Entropy Eigenvalues Monte Carlo method |
| Resumo: | 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 |
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