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Efficient point clouds based scatter correction for fully 3D PET

机译:基于高效点云的散点校正,用于全3D PET

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A novel way to perform scatter correction for Positron Emission Tomography by using point clouds representation is presented. The scatter correction method is based on single scatter simulation. The strategy of scatter point sampling during scatter calculation will affect the accuracy of scatter correction directly and the number of sampled scatter points determines the computation complexity. Compared with regular voxel based scatter point sampling, the new method, which has been greatly reduced in size, adopts content-adaptive point clouds structure. The point clouds method can capture both anatomical and functional information, and cover the critical regions with limited number of points. Reduced sampled points significantly bring down the computation cost. Experiments with Monte Carlo simulations prove that such process can reduce the time consumption while at the same time maintain the reconstruction accuracy at the same level.
机译:提出了一种利用点云表示法对正电子发射断层扫描进行散射校正的新方法。散点校正方法基于单点散点模拟。散点计算过程中的散点采样策略将直接影响散点校正的准确性,而采样的散点数决定了计算复杂度。与常规的基于体素的散点采样相比,新方法的大小已大大减小,采用了内容自适应点云结构。点云方法可以捕获解剖学信息和功能信息,并以有限的点数覆盖关键区域。减少的采样点显着降低了计算成本。蒙特卡洛模拟的实验证明,该过程可以减少时间消耗,同时将重建精度保持在相同水平。

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