Ricardo
Otazo1, Daniel K. Sodickson1
1Center for Biomedical Imaging, New
York University School of Medicine, New York, NY, United States
A
method to adapt the sparsifying transform in order to increase image sparsity
for compressed sensing (CS) is presented. The method updates the sparsifying
transform and computes the corresponding sparse coefficient simultaneously
using image examples from the undersampled data. We demonstrate improved
performance of adaptive CS over standard CS with a pre-defined wavelet
transform on a brain imaging example