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Abstract #1190

Fast Variable Density Poisson-Disc Sample Generation with Directional Variation for Compressed Sensing

Nicholas Dwork1, Corey A. Baron2, Ethan M. I. Johnson3, Daniel O'Connor4, John M. Pauly5, and Peder E.Z. Larson1
1Radiology and Biomedical Imaging, UCSF, San Francisco, CA, United States, 2Robarts Research, Western University, Ontario, ON, Canada, 3Biomedical Engineering, Northwestern University, Evanston, IL, United States, 4Mathematics and Statistics, University of San Francisco, San Francisco, CA, United States, 5Electrical Engineering, Stanford University, Stanford, CA, United States

We present a fast method for generating a variable density poisson-disc sampling pattern. A minimum parameter value is used to create a background grid array for keeping track of those points that might affect any new candidate point; this reduces the number of conflicts that must be checked before acceptance of a new point, thus reducing the number of computations required. We demonstrate the algorithm's ability to generate variable density poisson-disc sampling patterns where the variations in density are a function of direction. We further show that these sampling patterns are appropriate for compressed sensing applications.

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