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Deep learning-based denoising algorithm in comparison to iterative reconstruction and filtered back projection: a 12-reader phantom study.

Youngjune KimDong Yul OhWon ChangEunhee KangJong Chul YeKyeorye LeeHae Young KimYoung Hoon KimJi Hoon ParkYoon Jin LeeKyoung Ho Lee
Published in: European radiology (2021)
• Low-contrast detectability in the images denoised using the deep learning algorithm was non-inferior to that in the images reconstructed using standard algorithms. • The proposed deep learning algorithm showed similar profiles of physical measurements to advanced iterative reconstruction algorithm (ADMIRE).
Keyphrases
  • deep learning
  • convolutional neural network
  • image quality
  • machine learning
  • artificial intelligence
  • computed tomography
  • physical activity
  • magnetic resonance
  • dual energy
  • mental health
  • magnetic resonance imaging