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KIKI-net: cross-domain convolutional neural networks for reconstructing undersampled magnetic resonance images.

Taejoon EoYohan JunTaeseong KimJinseong JangHo-Joon LeeDosik Hwang
Published in: Magnetic resonance in medicine (2018)
KIKI-net exhibits superior performance over state-of-the-art conventional algorithms in terms of restoring tissue structures and removing aliasing artifacts. The results demonstrate that KIKI-net is applicable up to a reduction factor of 3 to 4 based on variable-density Cartesian undersampling.
Keyphrases
  • convolutional neural network
  • deep learning
  • magnetic resonance
  • machine learning
  • high resolution
  • magnetic resonance imaging
  • optical coherence tomography