Fast variable density Poisson-disc sample generation with directional variation for compressed sensing in MRI |
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Institution: | 1. Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX, 76019, USA;2. Computer Science & Engineering Department, Lehigh University, Bethlehem, PA, 18015, USA;3. Tencent AI Lab, Shenzhen, 518057, China |
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Abstract: | We present a fast method for generating random samples according to a variable density poisson-disc distribution. 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 according to a parameterized function, including patterns where the variations in density are a function of direction. We further show that these sampling patterns are appropriate for compressed sensing applications. Finally, we present a method to generate patterns with a specific acceleration rate. |
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