Regularization of Diffusion Tensor Maps Using a Non-Gaussian Markov Random Field Approach

M. Martin-Fernandez, C. Alberola-Lopez, J. Ruiz-Alzola, C.-F. Westin
Sixth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'03), Lecture Notes in Computer Science 2879
Pages 92-100
November 15-18, 2003

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Abstract

In this paper we propose a novel non-Gaussian MRF for regularization of tensor fields for fiber tract enhancement. Two entities are considered in the model, namely, the linear component of the tensor, i.e., how much line-like the tensor is, and the angle of the eigenvector associated to the largest eigenvalue. A novel, to the best of the author's knowledge, angular density function has been proposed. Closed form expressions of the posterior densities are obtained. Some experiments are also presented for which color-coded images are visually meaningful. Finally, a quantitative measure of regularization is also calculated to validate the achieved results based on an averaged measure of entropy.

(a) Color-coded image in original field. (b) Regularized field.

Reference

Martin-Fernandez M, Alberola-Lopez C, Ruiz-Alzola J, Westin CF. Regularization of diffusion tensor maps using a non-gaussian markov random field approach. In RE Ellis, TM Peters, eds., Sixth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'03), Lecture Notes in Computer Science 2879. Montreal, Canada: Springer Verlag, 2003;92-100.

Bibtex entry

@InProceedings{martin-fernandezMICCAI03,
  author         = {M. Martin-Fernandez and C. Alberola-Lopez and J.           
                   Ruiz-Alzola and  C.-F. Westin},                             
  title          = {Regularization of Diffusion Tensor Maps Using a            
                   Non-Gaussian Markov  Random Field Approach},                
  editor         = {R. E. Ellis and T. M. Peters},                             
  booktitle      = {Sixth International Conference on Medical Image Computing  
                   and  Computer-Assisted Intervention (MICCAI'03), Lecture    
                   Notes in Computer Science 2879},                            
  pages          = {92--100},                                                  
  year           = {2003},                                                     
  address        = {Montreal, Canada},                                         
  month          = {November 15--18},                                          
  publisher      = {Springer Verlag},                                          
  note           = {}
}

Grants

TIC2001-3808-C02, NIH P41-RR13218 (NAC), CIMIT

Research areas

DTMRI, Tensor

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