A Sophisticated Method for X-Ray Image-Based Knee Osteoarthritis Diagnosis Utilising Moblienetv3 Large

A common deteriorating joint condition that impacts millions of individuals worldwide is osteoarthritis. For optimal care and avoidance of its development, early and accurate identification is essential. Algorithms utilizing deep learning are currently showing promising outcomes in medical image analysis applications, such as disease categorization. Through the use of the MobileNetV3 architecture, a compact and effective convolutional neural network (CNN) created for deployment on devices with limited resources, such as smartphones, this study proposes a unique method for the categorization of knee osteoarthritis. The suggested approach entails building a deep learning model using MobileNetV3 and assembling a sizable dataset of knee X-ray images containing both knee osteoarthritic and healthy patients. To achieve accurate and trustworthy ground truth labeling, the dataset is tweaked and marked by qualified radiologists.