Nonrigid Registration of 3D Scalar, Vector and Tensor Medical Data
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
Fiber Tract Mapping from Diffusion Tensor MRI
VLSM '01 Proceedings of the IEEE Workshop on Variational and Level Set Methods (VLSM'01)
Hidden Markov Measure Field Models for Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Vector-Valued Image Regularization with PDEs: A Common Framework for Different Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
A riemannian approach to diffusion tensor images segmentation
IPMI'05 Proceedings of the 19th international conference on Information Processing in Medical Imaging
Entropy-Controlled Quadratic Markov Measure Field Models for Efficient Image Segmentation
IEEE Transactions on Image Processing
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Diffusion weighted magnetic resonance imaging is widely used in the study of the structure of the fiber pathways in brain white matter. In this work we present a new method for denoising intra---voxel axon fiber tracks. In order to improve local (voxelwise) estimations, we use the general---purpose segmentation method called Entropy---Controlled Quadratic Markov Measure Field Models. Our proposal is capable of spatially---regularize multiple axon fiber orientations (intra-voxel orientations). In order to provide the best as possible local axon orientations to our spatial regularization procedure, we evaluate two optimization methods for fitting a Diffusion Basis Function model. We present qualitative results on real human Diffusion Weighted MRI data where the ground---truth is not available, and we quantitatively validate our results by synthetic experiments.