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Impact of CT convolution kernel on robustness of radiomic features for different lung diseases and tissue types.

Sarah DenzlerDiem VuongMarta BogowiczMatea PavicThomas FrauenfelderSandra ThiersteinEric Innocents EbouletBritta MaurerJanine SchnieringHubert Szymon GabryśIsabelle Schmitt-OpitzMiklos PlessRobert FoersterMatthias GuckenbergerStephanie Tanadini-Lang
Published in: The British journal of radiology (2021)
The study presents to our knowledge the most complete analysis on the impact of convolution kernel on the robustness of CT-based radiomics for four relevant tissue types in three different lung diseases. .
Keyphrases
  • contrast enhanced
  • image quality
  • dual energy
  • computed tomography
  • neural network
  • healthcare
  • positron emission tomography
  • magnetic resonance
  • lymph node metastasis
  • squamous cell carcinoma