Pipeline of knee osteoarthritis grading pipeline, which includes knee joints detection and knee OA grading.
- Detecting two knee joints in X-ray images using a customized YOLOv2 model.
- Classifying the KL grade of detected knee joints with a novel ordinal loss.
Knee joint detection (DetJoint) and KL grading (ClsKL) training/testing datasets, as well as best models, can be downloaded from KneeXrayData, around 7G.
Please consider cite the paper if you use the code or data for your research.
@article{chen2019fully, title={Fully Automatic Knee Osteoarthritis Severity Grading Using Deep Neural Networks with a Novel Ordinal Loss}, author={Chen, Pingjun and Gao, Linlin and Shi, Xiaoshuang and Allen, Kyle and Yang Lin}, journal={Computerized Medical Imaging and Graphics},, volume={75}, pages={84--92}, year={2019}, doi={https://doi.org/10.1016/j.compmedimag.2019.06.002}, publisher={Elsevier} }