Classification Anterior and Posterior of Knee Osteoarthritis X-Ray Images Grade KL-2 Using Deep Learning with Random Brightness Augmentation

Osteoarthritis of the knee (KOA) is a narrowing of the joint space area (JSA) due to lack of fluid in the knee joint, resulting in pain when moving and when it is severe, the femur and tibia meet. Medical personnel and existing computer-based methods have been able to detect patients with X-rays but have not been able to detect where visually the posterior AJ is still wide while the anterior AJ is actually narrow, so that the patient still feels joint pain. A new approach is proposed for the classification of X-Ray Grade Kellgren-Lawrence (KL)-2 Osteoarthritis Initiative image datasets using Deep Learning Neural Networks (DCNN) by setting the Random Brightness Augmentation hyperparameter. The experimental results obtained X-Ray Grade KL-2 narrowing image classification “Anterior View KOA” and “Posterior View KOA” with training accuracy of 83.33% and validation accuracy of 54.69% at Random Brightness with a value of 30.