Background Imaging with large coil arrays is desirable for rapid imaging and high signal to noise ratio. Compressed sensing (CS) is a promising way to accelerate myocardial perfusion imaging [1]. However with increasing number of coils CS is costly in terms of memory and computation time. Coil compression methods for reconstructing cardiac cine data with parallel imaging have been proposed [2,3...

Motivation In general, computational problems become harder, when inputs are represented in a compressed form. Motivation In general, computational problems become harder, when inputs are represented in a compressed form. • Develop efficient algorithms on compressed data (strings, trees, pictures) that operate directly on compressed data without decompressing them first. • Prove lower bounds on...

The focus of this paper is to consider the compressed sensing problem. It is stated that the compressed sensing theory, under certain conditions, helps relax the Nyquist sampling theory and takes smaller samples. One of the important tasks in this theory is to carefully design measurement matrix (sampling operator). Most existing methods in the literature attempt to optimize a randomly initiali...