  Simultaneous multislice (SMS) imaging is a one of the acceleration technique
of magnetic resonance imaging. SMS requires accurate sensitivity distributions
in the slice plane for each receiving coil. This requirement is difficult to
satisfy in practice, limiting the applications of this imaging technique. Here,
images are reconstructed by applying deep learning and amplitude modulation to
each slice image. Simulation experiments show that image reconstruction can be
achieved for both real- and complex-valued images. Image quality tends to
decrease with increasing number of simultaneously acquired images. It is also
shown that a larger difference in the phase modulation coefficients between
slices tends to increase the quality of the reconstructed images. Simulation
experiments and initial MR imaging experiments show promising results for this
method.
