Radiology and Biomedical Imaging, University of California in San Francisco, San Francisco, California, 94158, USA.
Center for Functional and Metabolic Mapping, Western University, Ontario, Canada.
Magn Reson Imaging. 2021 Apr;77:186-193. doi: 10.1016/j.mri.2020.11.012. Epub 2020 Nov 21.
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.
我们提出了一种快速的方法，根据可变密度泊松圆盘分布生成随机样本。使用最小参数值创建一个背景网格数组，以跟踪可能影响任何新候选点的那些点；这减少了在接受新点之前必须检查的冲突数量，从而减少了所需的计算数量。我们展示了该算法根据参数化函数生成可变密度泊松圆盘采样模式的能力，包括密度变化是方向函数的模式。我们进一步表明，这些采样模式适用于压缩感知应用。最后，我们提出了一种生成具有特定加速度的模式的方法。
