Application of Compressed Sensing on Magnetic Resonance Imaging: A brief Survey

This paper provides a brief survey of application of compressive sampling or compressive sensing (CS) in a major biomedical imaging application such as magnetic resonance imaging (MRI). MRI has a time-consuming data collection process. CS is an emerging mathematical technique which enables us to reconstruct the image or signal from very few samples. Recently severe efforts are made to apply CS to MRI to speed up the acquisition process. Reducing the amount of data reduces the scan time which in turn reduces the time of exposition of patient to the magnetic fields. Various optimization algorithms are proposed for the reconstruction of MR images from small set of available data without compromising with the image quality. Aim of this paper is to provide a brief analysis of current trends in CS applied to MRI.