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Image-based shading correction for narrow-FOV truncated pelvic CBCT with deep convolutional neural networks and transfer learning.

Matteo RossiGabriele BelottiChiara PaganelliAndrea PellaAmelia BarcelliniPietro CerveriGuido Baroni
Published in: Medical physics (2021)
We demonstrated that shading correction obtaining CT-compatible data from narrow-FOV CBCTs acquired with a customized in-room system is possible. Moreover, the transfer learning approach proved particularly beneficial for such a shading correction approach.
Keyphrases
  • convolutional neural network
  • deep learning
  • image quality
  • computed tomography
  • rectal cancer
  • dual energy
  • magnetic resonance imaging
  • artificial intelligence