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Abstract #3796

CIRcular Cartesian UnderSampling (CIRCUS): A Variable Density 3D Cartesian Undersampling Strategy for Compressed Sensing and Parallel Imaging

Jing Liu1, David A. Saloner1

1University of California San Francisco, San Francisco, CA, United States

Compressed sensing (CS) and parallel imaging (PI) have been exploited to reduce scan time by undersampling k-space data, which is highly desirable for 3D applications that usually involve unreasonably long scan times. This study proposes a novel method for generating undersampling patterns for 3D Cartesian acquisition, providing easy implementation, flexible sampling patterns, and high accuracy of image reconstruction with CS&PI.