Syed M Arshad, Lee C Potter, Chong Chen, Yingmin Liu, Preethi Chandrasekaran, Christopher Crabtree, Matthew S Tong, Orlando P Simonetti, Yuchi Han, Rizwan Ahmad
PURPOSE: To present and assess an outlier mitigation method that makes free-running volumetric cardiovascular MRI (CMR) more robust to motion. METHODS: The proposed method, called compressive recovery with outlier rejection (CORe), models outliers in the measured data as an additive auxiliary variable. We enforce MR physics-guided group sparsity on the auxiliary variable, and jointly estimate it along with the image using an iterative algorithm. For evaluation, CORe is first compared to traditional compressed sensing (CS), robust regression (RR), and an existing outlier rejection method using two simulation studies...
May 10, 2024: Magnetic Resonance in Medicine