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An efficient dual-domain deep learning network for sparse-view CT reconstruction.

Chang SunYazdan SalimiNeroladaki AngelikiSana BoudabbousHabib Zaidi
Published in: Computer methods and programs in biomedicine (2024)
This work presents an efficient dual-domain learning network for sparse-view CT reconstruction on raw projection data from a commercial scanner. The study also provides insights for designing an organ-based image quality assessment pipeline for sparse-view reconstruction tasks, potentially benefiting organ-specific dose reduction by sparse-view imaging.
Keyphrases
  • image quality
  • deep learning
  • computed tomography
  • neural network
  • dual energy
  • contrast enhanced
  • positron emission tomography
  • working memory
  • machine learning
  • magnetic resonance imaging
  • convolutional neural network