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Weakly supervised deep learning for diagnosis of multiple vertebral compression fractures in CT.

Euijoon ChoiDoohyun ParkGeonhui SonSeongwon BakTaejoon EoDaemyung YounDosik Hwang
Published in: European radiology (2023)
• Our proposed weakly supervised method may have comparable or better performance than the supervised method for vertebral-level vertebral compression fracture classification. • The weakly supervised model could have classified cases with multiple vertebral compression fractures at the vertebral-level, even if the model was trained with image-level labels. • Our proposed method could help reduce radiologists' labour because it enables vertebral-level classification from image-level labels.
Keyphrases
  • deep learning
  • machine learning
  • bone mineral density
  • artificial intelligence
  • postmenopausal women
  • convolutional neural network
  • magnetic resonance imaging
  • magnetic resonance
  • image quality