Sparse Sampling and Fully-3D Fast Total Variation Based Imaging Reconstruction for Chemical Shift Imaging in Magnetic Resonance Spectroscopy
We propose a 3-dimensional sparse sampling reconstruction method, aiming for chemical shift imaging in magnetic resonance spectroscopy. The method is a Compressed Sensing (CS) method based on the interior point optimization technique that can substantially reduce the number of sampling points required, and the method has been tested successfully in hyperpolarized 13C experimental data using two different sampling strategies.
KeywordsImaging reconstruction Chemical shift imaging 3D Compressed Sensing Sparse sampling of MRSI data
Zigen Song’s research is supported in part by the National Natural Science Foundation of China under Grant No. 11672177.
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