Comparison of diverse compressed sensing algorithms in rapid magnetic resonance imaging - Jing, Jin (2011)
Magnetic Resonance Imaging (MRI) is basically a noninvasive medical imaging modality which is used in radiology to visualize detailed internal structure as well as the limited functions of the human body. The standard method to reconstruct MRI images is carried out by fully sampling the image in its Fourier transform domain, and then taking the inverse Fourier transform on this fully sampled grid. However, the speed of data collection in MRI is very slow, limited by both physical and physiological constraints. The concept of compressed sensing (CS) could be used to in MRI data acquisition so as to speed up the entire process by reducing the amount of measurements. Nowadays researchers all over the world have proposed many CS algorithms to achieve this common goal. On the other hand, rare researches are conducted so far to systematically compare the performance of these algorithms.