Blind Compressive Sensing Dynamic MRI with Sparse Dictionaries

Sajan Goud Lingala¹, Mathews Jacob¹

We propose an sparse blind compressive algorithm to learn dictionary atoms that are constrained to be sparse for accelerated dynamic MRI reconstruction. The sparsity promoting norm on the dictionary atoms penalizes the learning of noisy basis functions. We demonstrate through examples on free breathing cardiac data, that the proposed scheme results in superior image quality in comparison to the conventional blind CS scheme and methods with fixed dictionaries.