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Abstract #1247

CoSMo: Compressed Sensing Motion Correction for Coronary MRI

Mehdi Hedjazi Moghari *1, Mehmet Akakaya *,12, Alan O'Connor, 12, Peng Hu1, Vahid Tarokh2, Warren J. Manning1, Reza Nezafat1

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

We examine the feasibility of using compressed sensing to reduce artifacts due to respiratory motion. Respiratory motion causes image artifacts and ghosting in cardiac imaging. Respiratory navigators are one of the methods used to mitigate these artifacts for free-breathing scans, where k-space lines falling outside a pre-defined gating window are reacquired until the whole k-space is filled. In this study, we introduce CoSMo, a compressed sensing-based method for reconstructing images without having to reacquire k-space lines rejected by the navigator.