A deep learning framework for vertebral morphometry and Cobb angle measurement with external validation
Author:
Funder
Analytical Center for the Government of the Russian Federation
Publisher
Springer Science and Business Media LLC
Subject
Orthopedics and Sports Medicine,Surgery
Link
https://link.springer.com/content/pdf/10.1007/s00586-022-07245-4.pdf
Reference26 articles.
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2. Labrom FR, Izatt MT, Claus AP, Little JP (2021) Adolescent idiopathic scoliosis 3D vertebral morphology, progression and nomenclature: a current concepts review. Eur Spine J 30:1823–1834. https://doi.org/10.1007/s00586-021-06842-z
3. Al-Bashir AK, Al-Abed MA, Amari HK et al (2019) Computer-based Cobb angle measurement using deflection points in adolescence idiopathic scoliosis from radiographic images. Neural Comput Appl 31:1547–1561. https://doi.org/10.1007/s00521-018-3614-y
4. Štern D, Njagulj V, Likar B et al (2013) Quantitative vertebral morphometry based on parametric modeling of vertebral bodies in 3D. Osteoporos Int 24:1357–1368. https://doi.org/10.1007/s00198-012-2089-4
5. Neubert A, Fripp J, Engstrom C et al (2013) Three-dimensional morphological and signal intensity features for detection of intervertebral disc degeneration from magnetic resonance images. J Am Med Inform Assoc 20:1082–1090. https://doi.org/10.1136/amiajnl-2012-001547
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