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Minimum perceivable size difference: how well can radiologists visually detect a change in lung nodule size from CT images?

Justin SolomonLukas EbnerAndreas ChristeAlan PetersJaro MunzLaura LöbelenzJeremias KlausTaylor RichardsEhsan SameiJustus E Roos
Published in: European radiology (2020)
• For solid nodules, radiologists could visually detect a 25% change in volume with 95% accuracy for nodules having greater than 6.3-mm baseline diameter. • For ground-glass nodules, radiologists could visually detect a 25% change in volume with 95% accuracy for nodules having greater than 13.2-mm baseline diameter. • Accuracy in detecting a change in nodule size began to stabilize around 90-100% for nodules with larger baseline diameters (> 8 mm for solid nodules, > 12 mm for ground-glass nodules) and larger relative volume differences (>15% for solid nodules, > 25% for ground-glass nodules).
Keyphrases
  • artificial intelligence
  • computed tomography
  • magnetic resonance
  • deep learning
  • machine learning
  • optical coherence tomography
  • convolutional neural network