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Parallel MRI (e.g., SENSE, GRAPPA) accelerates the data acquisition in modern clinical scanners using multiple receiver coils. However, it results in more computational demands on general purpose computers. Coil compression is a promising way to address the computational cost and memory requirements associated with a large number of receiver coils. In this work, a novel FPGA based hardware accelerator is designed to perform coil compression using QR decomposition. In-vivo reconstruction results from 30 coil cardiac data set, show that the proposed accelerator elevates the speed and memory constraints while preserving the image quality.
Gul et al. (Wed,) studied this question.