Diffusion basis functions decomposition for estimating white matter intravoxel fiber geometry.
IEEE Trans Med Imaging
; 26(8): 1091-102, 2007 Aug.
Article
em En
| MEDLINE
| ID: mdl-17695129
In this paper, we present a new formulation for recovering the fiber tract geometry within a voxel from diffusion weighted magnetic resonance imaging (MRI) data, in the presence of single or multiple neuronal fibers. To this end, we define a discrete set of diffusion basis functions. The intravoxel information is recovered at voxels containing fiber crossings or bifurcations via the use of a linear combination of the above mentioned basis functions. Then, the parametric representation of the intravoxel fiber geometry is a discrete mixture of Gaussians. Our synthetic experiments depict several advantages by using this discrete schema: the approach uses a small number of diffusion weighted images (23) and relatively small b values (1250 s/mm2), i.e., the intravoxel information can be inferred at a fraction of the acquisition time required for datasets involving a large number of diffusion gradient orientations. Moreover our method is robust in the presence of more than two fibers within a voxel, improving the state-of-the-art of such parametric models. We present two algorithmic solutions to our formulation: by solving a linear program or by minimizing a quadratic cost function (both with non-negativity constraints). Such minimizations are efficiently achieved with standard iterative deterministic algorithms. Finally, we present results of applying the algorithms to synthetic as well as real data.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Encéfalo
/
Interpretação de Imagem Assistida por Computador
/
Aumento da Imagem
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Imageamento Tridimensional
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Imagem de Difusão por Ressonância Magnética
/
Fibras Nervosas Mielinizadas
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Limite:
Animals
Idioma:
En
Revista:
IEEE Trans Med Imaging
Ano de publicação:
2007
Tipo de documento:
Article
País de afiliação:
México
País de publicação:
Estados Unidos