Scoliosis and Knee Osteoarthritis Classification and Detection using X-Rays

Abstract

Medical imaging plays a pivotal role in the early detection and accurate classification of musculoskeletal disorders. This study focuses on the development of a robust and efficient system for the detection and classification of two prevalent musculoskeletal conditions: scoliosis and knee osteoarthritis, using X-ray images. Scoliosis is a lateral curvature of the spine, while knee osteoarthritis involves the degeneration of knee joint cartilage and underlying bone.The proposed system leverages state-of-the-art deep learning techniques to automatically detect and classify these conditions from X-ray images. The workflow involves three main stages: preprocessing, feature extraction, and classification. During preprocessing, the X-ray images are normalized, noise-reduced, and anatomical landmarks are identified for accurate alignment. Key Words: Detection and classification, knee osteoarthritis, ordinal classification, X-rays.