AI Analyzes Spinal X-Rays to Standardize Scoliosis Assessment

These measurements guide diagnosis, follow-up, and treatment planning, yet they are still performed largely by hand. Manual workflows are time-consuming and prone to variation between and within clinicians. To help address this challenge, researchers have developed an artificial intelligence system that aims to make scoliosis measurements more consistent on X-ray images.

Developed by researchers at National Taiwan University and Taipei Veterans General Hospital, the artificial intelligence (AI) system analyzes spinal X-rays to deliver standardized curvature measurements. It automatically identifies each vertebra, delineates its shape, and evaluates tilt before calculating overall spinal curvature. By automating vertebra selection, it targets a major source of variability in manual assessment.

The team evaluated the system using spinal radiographs from Taipei Veterans General Hospital. Against measurements by experienced specialists, the AI showed strong agreement. When two human observers differed by no more than 5 degrees, average differences between the AI and specialists ranged from approximately 2.3 to 3.4 degrees across the assessed curves. Overall, agreement between the AI and clinicians was comparable to agreement between two human observers.

An external validation examined whether the approach would generalize across institutions and imaging conditions. Without retraining, the system continued to perform well on a dataset collected under different acquisition settings. The study, published in IEEE Transactions on Medical Imaging in August, 2026, indicates the tool could support more reproducible scoliosis measurement while reducing time and variability inherent to manual methods.

“Our goal is not to replace clinical judgment, but to provide doctors with a reliable tool that can make scoliosis measurement more consistent and reduce the variability that can occur during manual assessment,” said I-Yun Lisa Hsieh, associate professor of civil engineering at National Taiwan University.

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