A fast and rigorous anisotropic smoothing method for DT-MRI

Author

Castano-Moraga, C.A. ; Lenglet, C. ; Deriche, R. ; Ruiz-Alzola, J.

Author_Institution

Departamento de Senales y Comunicaciones, Centro de Tecnologia Medica

fYear

2006

fDate

6-9 April 2006

Firstpage

93

Lastpage

96

Abstract

Tensors are nowadays an increasing research domain in different areas, especially in image processing, motivated for example by DT-MRI (diffusion tensor magnetic resonance imaging). In this paper, we exploit the theoretically well-founded differential geometrical properties of the space of multivariate normal distributions, where it is possible to define a Riemannian metric and express statistics on the manifold of symmetric positive definite matrices. We focus on the contributions of these tools to the anisotropic filtering and regularization of tensor fields. We present promising results on synthetic and real DT-MRI data

Keywords

biomedical MRI; medical image processing; smoothing methods; tensors; DT-MRI; Riemannian metric; anisotropic filtering; diffusion tensor magnetic resonance imaging; fast rigorous anisotropic smoothing method; image processing; multivariate normal distributions; regularization; symmetric positive definite matrices; Anisotropic filters; Anisotropic magnetoresistance; Covariance matrix; Diffusion tensor imaging; Eigenvalues and eigenfunctions; Filtering; Gaussian distribution; Smoothing methods; Symmetric matrices; Tensile stress;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Imaging: Nano to Macro, 2006. 3rd IEEE International Symposium on

Conference_Location

Arlington, VA

Print_ISBN

0-7803-9576-X

Type

conf

DOI

10.1109/ISBI.2006.1624860

Filename

1624860