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A fast implementation of the incremental backprojection algorithms for parallel beam geometries

机译:用于平行光束几何形状的增量反射算法的快速实现

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The incremental backprojection algorithm is a fast backprojection approach requiring only O(N) and O(N/sup 2/) multiplications in contrast to O(N/sup 2/) and O(N/sup 3/) multiplications for the Shepp and Logan's backprojection algorithm in 2D and 3D backprojections, respectively, for each view. However, the improvement achieved by the incremental algorithm in practice was not so significant as expected in theory due to inevitably visiting pixels outside the beam in the searching flow scheme originally developed for the Incremental algorithm. To optimize implementation of the incremental algorithm, an efficient scheme, namely, coded searching flow scheme, is proposed in this paper to minimize the overhead caused by searching for all pixels in a beam. The key idea of this scheme is to encode the searching flow for all pixels inside each beam. While backprojection, all pixels may be visited without any overhead due to using the coded searching flow as the a priori information. The proposed coded searching flow scheme has been implemented on a Sun Sparc 10 and a Sun Sparc 20 workstations. The implementation results show that the proposed scheme is 1.45-2.0 times faster than the original searching flow scheme for most cases tested. Compared to the conventional Shepp and Logan's backprojection algorithm, the proposed scheme may achieve 5-8 and 3 times speed-ups for 2D and 3D backprojection, respectively.
机译:增量反冲算法是一种快速反扩展方法,只需要O(n)和o(n / sup 2 /)乘法与shepp的o(n / sup 2 /)和o(n / sup 3 /)乘法相比逻辑分别为2D和3D反冲分别为每个视图的反投影算法。然而,由于在最初为增量算法开发的搜索流程方案之外的光束以外的不可避免地访问像素,因此在实践中实现的增量算法实现的改进并不如预期的。为了优化增量算法的实现,在本文中提出了一种有效的方案,即编码的搜索流程方案,以最小化通过搜索波束中的所有像素而引起的开销。该方案的关键思想是为每个波束内的所有像素进行编码搜索流程。虽然背部分析,但由于使用编码搜索流作为先验信息,可以访问所有像素而没有任何开销。所提出的编码搜索流程方案已经在Sun Sparc 10和Sun Sparc 20工作站上实现。实施结果表明,对于大多数情况测试,所提出的方案比原始搜索流程更快1.45-2.0倍。与传统的SHEPP和LogAn的反投影算法相比,所提出的方案分别可以分别实现2D和3D反冲的加速5-8和3次。

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