利用反向传播神经网络在大规模并行SIMD计算机上实现SPECT重建

J. Kerr, E. Bartlett
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引用次数: 7

摘要

研究了利用反向传播神经网络的并行实现重建单光子发射计算机断层扫描(SPECT)图像的可行性。MasPar MP-1是一个单指令多数据(SIMD)大规模并行机器,由128*128的4位处理器阵列组成。神经网络分布在阵列上,每个节点和网络的每个互连都有一个处理器。一个8*8的SPECT图像切片被投影到8个平面上。结果表明,基于投影的神经网络可以准确地生成原始SPECT切片图像。同样,当在两个平行的切片上进行训练时,神经网络能够将未经训练的中心图像复制到均方根误差为0.001928的水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SPECT reconstruction using a backpropagation neural network implemented on a massively parallel SIMD computer
The feasibility of reconstructing a single photon emission computed tomography (SPECT) image via the parallel implementation of a backpropagation neural network is shown. The MasPar MP-1 is a single-instruction multiple-data (SIMD) massively parallel machine, composed of a 128*128 array of 4-bit processors. The neural network is distributed on the array by dedicating a processor to each node and each interconnection of the network. An 8*8 SPECT image slice section is projected into eight planes. It is shown that, based on the projections, the neural network can produce the original SPECT slice image exactly. Likewise, when trained on two parallel slices, separated by one slice, the neural network is able to reproduce the center, untrained image to an RMS (root mean square) error of 0.001928.<>
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