Automatic hip osteoarthritis grading with uncertainty estimation from computed tomography using digitally-reconstructed radiographs
Author:
Funder
Japan Society for the Promotion of Science
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11548-024-03087-1.pdf
Reference31 articles.
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2. Günther KP, Sun Y (1999) Reliability of radiographic assessment in hip and knee osteoarthritis. Osteoarthr Cartil 7(2):239–246. https://doi.org/10.1053/joca.1998.0152
3. Damen J, Schiphof D, Wolde ST, Cats HA, Bierma-Zeinstra SMA, Oei EHG (2014) Inter-observer reliability for radiographic assessment of early osteoarthritis features: the check (cohort hip and cohort knee) study. Osteoarthr Cartil 22(7):969–974. https://doi.org/10.1016/j.joca.2014.05.007
4. Üreten K, Arslan T, Gültekin KE, Demir AND, Özer HF, Bilgili Y (2020) Detection of hip osteoarthritis by using plain pelvic radiographs with deep learning methods. Skelet Radiol 49:1369–1374. https://doi.org/10.1007/s00256-020-03433-9
5. von Schacky CE, Sohn JH, Liu F, Ozhinsky E, Jungmann PM, Nardo L, Posadzy M, Foreman SC, Nevitt MC, Link TM, Pedoia V (2020) Development and validation of a multitask deep learning model for severity grading of hip osteoarthritis features on radiographs. Radiology 295(1):136–145. https://doi.org/10.1148/radiol.2020190925
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