Scoliosis and Knee Osteoarthritis Classification and Detection using X-Rays

Scoliosis and Knee Osteoarthritis Classification and Detection using X-Rays

Sahil Dinesh Patil*1, Aparna Todkar*2, Adib Shaikh*3, Kashif Shaikh*4, Mushfiq Momin*5.

1,3,4,5Student, Computer Engineering, Sinhgad Academy of Engineering, Kondhwa, Pune, Maharashtra,

India. 2Professor, Department Of Computer Engineering, Sinhgad Academy Of Engineering, Kondhwa, Pune, Maharashtra, India.

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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.