Radiol Artif Intell 2020 May 27;2(3):e180063. Epub 2020 May 27.
Department of Software and IT Engineering, Ecole de Technologie Supérieure, 1100 rue Notre-Dame Ouest, Montréal, QC, Canada H3C 1K3 (H.K., L.D.); Division of Orthopedics, Sainte-Justine Hospital, Montréal, Canada (J.J., C.B., I.N., O.C., S.P., G.G., H.L.); and Department of Surgery, Université de Montréal, Montréal, Canada (M.L.N., S.P., G.G., H.L.).
Purpose: To develop an automatic method for the assessment of the Risser stage using deep learning that could be used in the management panel of adolescent idiopathic scoliosis (AIS).
Materials And Methods: In this institutional review board approved-study, a total of 1830 posteroanterior radiographs of patients with AIS (age range, 10-18 years, 70% female) were collected retrospectively and graded manually by six trained readers using the United States Risser staging system. Each radiograph was preprocessed and cropped to include the entire pelvic region. Read More