Deep Learning based Knee OsteoArthritis Grade Classification: A Review

State-of-the-art methods for knee OsteoArthritis (OA) disease grade classification using Deep learning (DL) based techniques are reviewed in the current work. Early detection-cum-classification of the knee is of substantial learning on X-ray and magnetic resonance (MR) images. Further classification allows estimating the great civility which is utilized for accessing the disease progression topics in the scope including various data set experiments and the performance evaluation metrics. The purpose of the current work is to introduce the methods in the field and highlight the shortcomings to be addressed as potential considerations in clinical practices the need for better preprocessing techniques and experimentation on the classification model is summarized at the end. Furthermore, the review concludes the published work in terms of highest performance and future work in the direction of improving classification accuracy.