Kane WJ (1977) Scoliosis prevalence: a call for a statement of terms. Clin Orthop Relat Res 126:43–46

Google Scholar 

Rose LD, Williams R, Ajayi B, Abdalla M, Bernard J, Bishop T, Papadakos N, Lui DF (2023) Reducing radiation exposure and cancer risk for children with scoliosis: EOS the new gold standard. Spine Deform. https://doi.org/10.1007/s43390-023-00653-6

Article  PubMed  PubMed Central  Google Scholar 

Willner S (1979) Moiré topography for the diagnosis and documentation of scoliosis. Acta Orthop Scand. https://doi.org/10.3109/17453677908989770

Article  PubMed  Google Scholar 

Porto F, Gurgel JL, Russomano T, Farinatti PDTV (2010) Moiré topography: characteristics and clinical application. Gait Posture. https://doi.org/10.1016/j.gaitpost.2010.06.017

Article  PubMed  Google Scholar 

Treuillet S, Lucas Y, Crepin G, Peuchot B, Pichaud JC (2002) SYDESCO: a laser-video scanner for 3D scoliosis evaluations. Stud Health Technol Inf 3:70–73

Google Scholar 

Knott P, Mardjetko S, Nance D, Dunn M (2006) Electromagnetic topographical technique of curve evaluation for adolescent idiopathic scoliosis. Spine (Phila Pa 1976). https://doi.org/10.1097/01.brs.0000245924.82359.ab

Article  PubMed  Google Scholar 

Manca A, Monticone M, Cugusi L, Doria C, Tranquilli-Leali P, Deriu F (2018) Back surface measurements by rasterstereography for adolescent idiopathic scoliosis: from reproducibility to data reduction analyses. Eur Spine J. https://doi.org/10.1007/s00586-018-5645-6

Article  PubMed  Google Scholar 

Drerup B (2014) Rasterstereographic measurement of scoliotic deformity. Scoliosis. https://doi.org/10.1186/s13013-014-0022-7

Article  PubMed  PubMed Central  Google Scholar 

Liu XC, Thometz JG, Lyon RM, Klein J (2001) Functional classification of patients with idiopathic scoliosis assessed by the quantec system: a discriminant functional analysis to determine patient curve magnitude. Spine (Phila Pa 1976). https://doi.org/10.1097/00007632-200106010-00020

Article  PubMed  Google Scholar 

Watanabe K, Aoki Y, Matsumoto M (2019) An application of artificial intelligence to diagnostic imaging of spine disease: estimating spinal alignment from moiré images. Neurospine. https://doi.org/10.14245/ns.1938426.213

Article  PubMed  PubMed Central  Google Scholar 

Yang J, Zhang K, Fan H, Huang Z, Xiang Y, Yang J, He L, Zhang L, Yang Y, Li R, Zhu Y, Chen C, Liu F, Yang H, Deng Y, Tan W, Deng N, Yu X, Xuan X, Xie X, Liu X, Lin H (2019) Development and validation of deep learning algorithms for scoliosis screening using back images. Commun Biol. https://doi.org/10.1038/s42003-019-0635-8

Article  PubMed  PubMed Central  Google Scholar 

Colombo T, Mangone M, Agostini F, Bernetti A, Paoloni M, Santilli V, Palagi L (2021) Supervised and unsupervised learning to classify scoliosis and healthy subjects based on non-invasive rasterstereography analysis. Plos one 16(12):e0261511

Article  CAS  PubMed  PubMed Central  Google Scholar 

Weiss H, Seibel S (2013) Can surface topography replace radiography in the management of patients with scoliosis? Hard Tissue. https://doi.org/10.13172/2050-2303-2-2-437

Article  Google Scholar 

Tabard-Fougère A, Bonnefoy-Mazure A, Hanquinet S, Lascombes P, Armand S, Dayer R (2017) Validity and reliability of spine rasterstereography in patients with adolescent idiopathic scoliosis. Spine. https://doi.org/10.1097/BRS.0000000000001679

Article  PubMed  Google Scholar 

Bassani T, Stucovitz E, Galbusera F, Brayda-Bruno M (2019) Is rasterstereography a valid noninvasive method for the screening of juvenile and adolescent idiopathic scoliosis? Eur Spine J (3). https://doi.org/10.1007/s00586-018-05876-0

Kim HE, Cosa-Linan A, Santhanam N, Jannesari M, Maros ME, Ganslandt T (2022) Transfer learning for medical image classification: a literature review. BMC Med Imaging. https://doi.org/10.1186/s12880-022-00793-7

Article  PubMed  PubMed Central  Google Scholar 

Parsons VL (2017) Stratified sampling. Anonymous. Wiley StatsRef: Statistics Reference Online, New York, pp 1–11

Google Scholar 

Paszke A, Gross S, Massa F, Lerer A, Bradbury J, Chanan G, Killeen T, Lin Z, Gimelshein N, Antiga L (2019) Pytorch: an imperative style, high-performance deep learning library. Curran Associates Inc, New York

Google Scholar 

Carman DL, Browne RH, Birch JG (1990) Measurement of scoliosis and kyphosis radiographs. Intraobs Interobs Var 72(3):328–33

CAS  Google Scholar 

Gstoettner M, Sekyra K, Walochnik N, Winter P, Wachter R, Bach CM (2007) Inter- and intraobserver reliability assessment of the Cobb angle: manual versus digital measurement tools. Eur Spine J. https://doi.org/10.1007/s00586-007-0401-3

Article  PubMed  PubMed Central  Google Scholar