Abstract #1092

Non-Iterative Motion-Error Regularized Reconstruction for Efficient Respiratory Gating with Auto-Calibrating Parallel Imaging

Peng Lai¹, Joseph Yitan Cheng², Shreyas S Vasanawala², and Anja C.S Brau³

¹Global MR Applications and Workflow, GE Healthcare, Menlo Park, CA, United States, ²Radiology, Stanford University, Stanford, CA, United States, ³Global MR Applications and Workflow, GE Healthcare, Munich, Germany

Respiratory gating (RG) is commonly used for free-breathing 3D MRI. Conventional RG based on acceptance/rejection performs hard-threshholding on acquired data and suffers from either increased motion corruption with a large acceptance window or long scan time/increased undersampling artifacts with a small window. This work developed a non-iterative respiratory soft-threshholding method by incorporating the motion-induced error into autocalibrating parallel imaging (ac-PI). The proposed method showed more effective motion suppression on free-breathing 3D cine than conventional respiratory gating on the same datasets. This method can be generalized to suppress other types of motion with full acquisition or ac-PI as well.

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