Parallel Compressed Sensing method to accelerate MRI

MRI is a breakthrough technology in medical diagnosis, but has a critical disadvantage of slow processing. Among the techniques used to accelerate the process of conventional MRI, SENSitivity Encoding (SENSE) is the most popular one. Also, the development of Compressed Sensing (CS) method has contributed to decrease the processing time of MRI. Both CS and SENSE accelerate conventional MRI by reducing the number of collected data and the combination of the two techniques can tremendously accelerate MRI setting time. In this paper, we propose a method combining the two techniques to accelerate conventional MRI, named p-CS. This method first uses CS to reconstruct a set of aliased images with a field of view (FOV) in each coil and applies the basic SENSE algorithm to produce the final full image. The empirical results show that signal-to-noise ratio (SNR) of the image obtained by this method is larger than that those of other methods.

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