Scoliosis Assessment

Scoliosis assessment aims to accurately measure spinal curvature for diagnosis and monitoring, traditionally relying on X-rays which pose radiation risks. Current research focuses on developing non-invasive alternatives, employing deep learning models (e.g., convolutional neural networks) to analyze gait patterns from video or automate Cobb angle measurements from ultrasound and DXA scans. These automated methods aim to improve accuracy, reduce inter-observer variability, and minimize radiation exposure, ultimately enhancing the efficiency and safety of scoliosis diagnosis and management.