K-t Group Sparse using Intensity Based Clustering

Claudia Prieto¹, Muhammad Usman¹, Eike Nagel¹, Philip Batchelor¹, Tobias Schaeffter¹

K-t Group Sparse (k-t GS) has been recently introduced to achieve high acceleration factors in dynamic-MRI. Kt-GS exploits not just the sparsity of dynamic-MRI but also the spatial group structure of the x-f space. However, it presents two drawbacks: a) an additional training-scan is required for group assignment, and b) the group assignment is based only on the connectivity of neighbouring pixels using a time-consuming hard thresholding scheme. Here we propose to modify k-t GS by using the intensity order, estimated from the same acquired data, for a more robust group assignment. This approach has been tested in cine and perfusion cardiac images with acceleration factors up to 9.