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A computationally efficient reconstruction algorithm for circular cone-beam computed tomography using shallow neural networks
Moreover, we show that the training time of an NN-FDK network is orders of magnitude lower than the considered deep neural networks, with only a slight reduction in reconstruction accuracy.
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