Accelerating Dynamic Contrast-Enhanced MRI Using Compressed Sensing

Compressed Sensing (CS) has emerged as an effective approach to fast magnetic resonance imaging [1-3]. By taking advantage of the signal sparsity in a transformed domain, an image can be reconstructed from k-space signals sampled below the Nyquist rate. In the CS imaging, sparsifying transform plays a key role in the reconstruction algorithm. In this study, we developed a dynamic CS imaging method that utilizes a temporal difference operator to enhance the image sparsity. The new method was assessed using simulated and in vivo dynamic MRI data where the temporal difference images are sparse by nature.