Automatic diagnosis of knee osteoarthritis severity using Swin transformer
Author:
Affiliation:
1. INTTIC, DZ
2. Université d'Orléans, FR
3. Université d'Orléans, France, FR
4. University of Orleans, FR
5. IULM university, IT
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3617233.3617234
Reference20 articles.
1. Automatic Detection of Knee Joints and Quantification of Knee Osteoarthritis Severity Using Convolutional Neural Networks
2. Quantifying radiographic knee osteoarthritis severity using deep convolutional neural networks
3. A decision support tool for early detection of knee OsteoArthritis using X-ray imaging and machine learning: Data from the OsteoArthritis Initiative
4. Yun-Hao Cao , Hao Yu , and Jianxin Wu . 2022 . Training vision transformers with only 2040 images. In Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022 , Proceedings, Part XXV. Springer, 220–237 . Yun-Hao Cao, Hao Yu, and Jianxin Wu. 2022. Training vision transformers with only 2040 images. In Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part XXV. Springer, 220–237.
5. Fully automatic knee osteoarthritis severity grading using deep neural networks with a novel ordinal loss
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