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Reproducibility of a semiautomatic lobar lung tissue assignment technique on noncontrast CT scans: a study on swine animal model.

Nile LuuNathan VanAlireza ShojazadehYixiao ZhaoSabee Molloi
Published in: European radiology experimental (2024)
• Lobar segmentation is essential for precise disease assessment and treatment planning. • Current methods for segmentation using fissure lines are problematic. • The minimum-cost-path technique here is proposed and a swine model showed excellent reproducibility for lobar mass measurements. • Interobserver agreement was excellent, with intraclass correlation coefficients greater than 0.90.
Keyphrases
  • dual energy
  • deep learning
  • convolutional neural network
  • computed tomography
  • contrast enhanced
  • image quality
  • magnetic resonance imaging
  • positron emission tomography
  • magnetic resonance
  • machine learning