Adaptive Noise Filtering for Accurate and Precise Diffusion Estimation in Fiber Crossings

Autor:	Arjan den Dekker, Ganesh Khedoe, Frans M. Vos, Kees A. Grimbergen, Dirk H. J. Poot, Matthan W.A. Caan, Lucas J. van Vliet, Silvia D. Olabarriaga
Rok vydání:	2010
Předmět:	Adaptive filter symbols.namesake Mathematical optimization Minimum mean square error Gaussian noise Rician fading Gaussian function symbols Kernel adaptive filter Estimator Filter (signal processing) Algorithm Mathematics
Zdroj:	Medical Image Computing and Computer-Assisted Intervention – MICCAI 2010 ISBN: 9783642157042 MICCAI (1)
Popis:	Measuring the diffusion properties of crossing fibers is very challenging due to the high number of model parameters involved and the intrinsically low SNR of Diffusion Weighted MR Images. Noise filtering aims at suppressing the noise while pertaining the data distribution. We propose an adaptive version of the Linear Minimum Mean Square Error (LMMSE) estimator to achieve this. Our filter applies an adaptive filtering kernel that is based on a space-variant estimate of the noise level and a weight consisting of the product of a Gaussian kernel and the diffusion similarity with respect to the central voxel. The experiments show that the data distribution after filtering is still Rician and that the diffusivity values are estimated with a higher precision while pertaining an equal accuracy. We demonstrate on brain data that our adaptive approach performs better than the initial LMMSE estimator.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::5245b8bac4faa61b114c7690ec0af5ac https://doi.org/10.1007/978-3-642-15705-9_21 Zobrazit plný text záznamu