An experiment of parallel SPECT data reconstruction

E. L. Piccolomini, F. Zama
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引用次数: 2

Abstract

In this work we use a massively parallel architecture for solving the problem of reconstructing human brain sections from experimental data obtained from a Gamma camera equipped with parallel-hole collimators. We compute least-squares regularized solutions by means of weighted conjugate gradient iterations coupled with a suitable stopping rule. The computations are distributed to the CRAY T3E parallel processors following two different decomposition strategies obtaining high speed up values. This decomposition strategy can be easily extended to a wide family of iterative reconstruction algebraic methods.
并行SPECT数据重建实验
在这项工作中,我们使用大规模并行架构来解决从配备平行孔准直器的伽玛相机获得的实验数据重建人脑切片的问题。我们用加权共轭梯度迭代和合适的停止规则来计算最小二乘正则解。根据两种不同的分解策略,将计算分配到CRAY T3E并行处理器上,从而获得较高的加速值。这种分解策略可以很容易地扩展到一系列迭代重构代数方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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