Feature Learning to Automatically Assess Radiographic Knee Osteoarthritis Severity
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-42750-4_2
Reference88 articles.
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2. Thomson, J., ONeill, T., Felson, D., Cootes, T.: Automated shape and texture analysis for detection of osteoarthritis from radiographs of the knee. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 127–134. Springer (2015)
3. Shamir, L., Ling, S.M., Scott, W., Hochberg, M., Ferrucci, L., Goldberg, I.G.: Early detection of radiographic knee osteoarthritis using computer-aided analysis. Osteoarthr. Cartil. 17(10), 1307–1312 (2009)
4. Shamir, L., Orlov, N., Eckley, D.M., Macura, T., Johnston, J., Goldberg, I.G.: WNDCHARM—an open source utility for biological image analysis. Source Code Biol. Med. 3(1), 13 (2008)
5. Orlov, N., Shamir, L., Macura, T., Johnston, J., Eckley, D.M., Goldberg, I.G.: WND-CHARM: multi-purpose image classification using compound image transforms. Pattern Recognit. Lett. 29(11), 1684–1693 (2008)
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