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Abstract #0349

Compressed Sensing with Transform Domain Dependencies for Coronary MRI

Mehmet Akakaya1,2, Seunghoon Nam1,2, Peng Hu2, Warren Manning2, Vahid Tarokh1, Reza Nezafat2

1Harvard University, Cambridge, MA, United States; 2Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States

Lengthy acquisition time is one of the main limitations of coronary MRI. Parallel imaging has been used to accelerate image acquisition but with limited success due to low signal-to-noise ratio. Compressed sensing (CS) has been recently utilized to accelerate image acquisition in MRI, but its use in cardiac MRI has been limited due to blurring artifacts. In this study, we develop an improved CS reconstruction method that uses the dependencies of transform domain coefficients to reduce the observed blurring and reconstruction artifacts in coronary MRI.