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SPECT reconstruction using a backpropagation neural network implemented on a massively parallel SIMD computer

机译:使用在大规模并行SIMD计算机上实现的反向传播神经网络进行SPECT重建

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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.
机译:显示了通过反向传播神经网络的并行实现重建单个光子发射计算机断层扫描(SPECT)图像的可行性。 MasPar MP-1是单指令多数据(SIMD)大规模并行计算机,由128位* 128阵列的4位处理器组成。通过将处理器专用于网络的每个节点和每个互连,将神经网络分布在阵列上。将一个8 * 8 SPECT图像切片部分投影到八个平面中。结果表明,基于这些投影,神经网络可以准确地产生原始的SPECT切片图像。同样,当在两个平行的切片上训练时,由一个切片隔开,神经网络能够将未经训练的中心图像重现为RMS(均方根)误差0.001928。

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