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

Abstract

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.<>