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Image quality of ultralow-dose chest CT using deep learning techniques: potential superiority of vendor-agnostic post-processing over vendor-specific techniques.

Ju Gang NamChulkyun AhnHyewon ChoiWonju HongJongsoo ParkJong Hyo KimJin Mo Goo
Published in: European radiology (2021)
• A vendor-agnostic deep learning post-processing algorithm applied to ultralow-dose chest CT exhibited the best image quality compared to vendor-specific deep learning algorithm and ASiR techniques. • Two out of three readers preferred a vendor-agnostic deep learning post-processing algorithm in comparison to vendor-specific deep learning algorithm and ASiR techniques. • A vendor-specific deep learning reconstruction algorithm yielded the least image noise, but showed significantly more frequent specific distortion artifacts and increased skewness of attenuation compared to a vendor-agnostic algorithm.
Keyphrases
  • deep learning
  • image quality
  • artificial intelligence
  • convolutional neural network
  • computed tomography
  • machine learning
  • dual energy
  • magnetic resonance imaging
  • human health