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Assessment of rapidly advancing bone age during puberty on elbow radiographs using a deep neural network model.

Kyung-Sik AhnByeonguk BaeWoo Young JangJin Hyuck LeeSaelin OhBaek Hyun KimSi Wook LeeHae Woon JungJae Won LeeJinkyeong SungKyu-Hwan JungChang Ho KangSoon Hyuck Lee
Published in: European radiology (2021)
• Bone age during puberty is particularly important for patients with scoliosis or limb-length discrepancy to determine the phase of the disease, which influences the timing and method of surgery. • The commonly used hand radiographs-based methods have limitations in assessing bone age during puberty due to the less prominent morphological changes of the hand and wrist bones in this period. • A deep neural network model trained with elbow radiographs exhibited similar performance to human experts on estimating rapidly advancing bone age during puberty.
Keyphrases
  • neural network
  • bone mineral density
  • soft tissue
  • bone loss
  • bone regeneration
  • postmenopausal women
  • minimally invasive
  • surgical site infection