Automatic detection and classification of knee osteoarthritis using deep learning approach
Author:
Publisher
Springer Science and Business Media LLC
Subject
Radiology, Nuclear Medicine and imaging,General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s11547-022-01476-7.pdf
Reference28 articles.
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2. Cross M, Smith E, Hoy D, Nolte S, Ackerman I, Fransen M, Bridgett L, Williams S et al (2014) The global burden of hip and knee osteoarthritis: estimates from the global burden of disease 2010 study. Ann Rheum Dis 73:1323–1330. https://doi.org/10.1136/annrheumdis-2013-204763
3. Karsdal MA, Michaelis M, Ladel C, Siebuhr AS, Bihlet AR, Andersen JR et al (2016) Disease-modifying treatments for osteoarthritis (DMOADs) of the knee and hip: lessons learned from failures and opportunities for the future. Osteoarthritis Cartilage 24:2013–2021. https://doi.org/10.1016/j.joca.2016.07.017
4. Altman R, Brandt K, Hochberg M, Moskowitz R, Bellamy N, Bloch DA et al (1996) Design and conduct of clinical trials in patients with osteoarthritis: recommendations from a task force of the osteoarthritis research society: results from a workshop. Osteoarthritis Cartilage 4:217–243. https://doi.org/10.1016/S1063-4584(05)80101-3
5. Tiulpin A, Thevenot J, Rahtu E, Lehenkari P, Saarakkala S (2018) Automatic knee osteoarthritis diagnosis from plain radiographs: a deep learning-based approach. Sci Rep 8:1727. https://doi.org/10.1038/s41598-018-20132-7
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