Reconstructing diffusion kurtosis tensors from sparse noisy measurements

Yugang Liu, Siming Wei, Quan Jiang, Yizhou Yu
2010 2010 IEEE International Conference on Image Processing  
Diffusion kurtosis imaging (DKI) is a recent MRI based method that can quantify deviation from Gaussian behavior using a kurtosis tensor. DKI has potential value for the assessment of neurologic diseases. Existing techniques for diffusion kurtosis imaging typically need to capture hundreds of MRI images, which is not clinically feasible on human subjects. In this paper, we develop robust denoising and model fitting methods that make it possible to accurately reconstruct a kurtosis tensor from
more » ... or less noisy measurements. Our denoising method is based on subspace learning for multi-dimensional signals and our model fitting technique uses iterative reweighting to effectively discount the influences of outliers. The total data acquisition time thus drops significantly, making diffusion kurtosis imaging feasible for many clinical applications involving human subjects.
doi:10.1109/icip.2010.5649554 dblp:conf/icip/LiuWJY10 fatcat:qa62qv6pbzak5bqfpasklenlb4