Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
Rician noise removal in diffusion tensor MRI
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Color TV: total variation methods for restoration of vector-valued images
IEEE Transactions on Image Processing
ML parameter estimation for Markov random fields with applications to Bayesian tomography
IEEE Transactions on Image Processing
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Detailed assessment of myocardial motion provides a key indicator of ventricular function, enabling the early detection and assessment of a range of cardiac abnormalities. Existing techniques for myocardial contractility analysis are complicated by a combination of factors including resolution, acquisition time, and consistency of quantification results. Phase-contrast velocity MRI is a technique that provides instantaneous, in vivomeasurement of tissue velocity on a per-voxel basis. It allows for the direct derivation of contractile indices with minimal post-processing. For this method to be clinically useful, SNR and image artifacts need to be addressed. The purpose of this paper is to present a Maximum a posteriori(MAP) restoration technique for high quality myocardial motion recovery. It employs an accurate noise modeling scheme and a generalized Gaussian Markov random field prior tailored for the myocardial morphology. The quality of the proposed method is evaluated with both simulated myocardial velocity data with known ground truth and in vivophase-contrast MR velocity acquisitions from a group of normal subjects.