Deep Convolutional Neural Network for Low Projection SPECT Imaging
  Reconstruction
  In this paper, we present a novel method for tomographic image reconstruction
in SPECT imaging with a low number of projections. Deep convolutional neural
networks (CNN) are employed in the new reconstruction method. Projection data
from software phantoms were used to train the CNN network. For evaluation of
the efficacy of the proposed method, software phantoms and hardware phantoms
based on the FOV SPECT system were used. The resulting tomographic images are
compared to those produced by the "Maximum Likelihood Expectation Maximisation"
(MLEM).
