Shoulder Radiograph

Shoulder radiograph analysis is crucial for diagnosing musculoskeletal diseases, but interpreting these images can be challenging due to bone overlap and subtle findings. Current research focuses on developing deep learning models, particularly convolutional neural networks (CNNs) and generative adversarial networks (GANs), to improve diagnostic accuracy and automate tasks like bone layer separation, lesion detection, and severity scoring (e.g., for rotator cuff tears or osteoarthritis). These advancements aim to enhance diagnostic consistency, reduce radiologist workload, and improve the efficiency and accessibility of orthopedic care.