Scoliosis is a complex spine deformity with direct functional and cosmetic impacts on the individual. The reference standard for assessing scoliosis severity is the Cobb angle which is measured on radiographs by human specialists, carrying interobserver variability and inaccuracy of measurements. These limitations may result in lack of timely referral for management at a time the scoliotic deformity progression can be saved from surgery. We aimed to create a machine learning (ML) model for automatic calculation of Cobb angles on 3-foot standing spine radiographs of children and adolescents with clinical suspicion of scoliosis (AIS) across two clinical scenarios (idiopathic, group 1 and congenital scoliosis, group 2).
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Meeting name:
SPR 2024 Annual Meeting & Postgraduate Course
, 2024
Authors:
Stott Samantha,
Wu Yujie,
Hosseinpour Shahob,
Chen Chaojun,
Namdar Khashayar,
Amirabadi Afsaneh,
Shroff Manohar,
Khalvati Farzad,
Doria Andrea
Keywords:
Radiograph,
Children