Regularization of Diffusion Tensor Maps Using a Non-Gaussian Markov Random Field Approach
- Topics:
- Healthcare Services
- Source:
- Springer Science+Business Media
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Overview: This paper proposes 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.
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Format: PDF | Size: 224KB | Date: Nov 2003 | Pages: 9
