Multi-parameter scoliosis evaluation from dual-view x-rays via a local sine-based projection model.

Objective. To develop a robust and accurate multi-parameter assessment framework for adolescent idiopathic scoliosis based on spinal x-ray images, overcoming the limitations of traditional Cobb angle (CA)-based evaluation.Approach. We proposed a dual-view labeling protocol and employed a Residual U-Net architecture to segment vertebral bodies in 700 paired anteroposterior and lateral x-rays. A novel Local Sine-based Spinal Projection Model was introduced to calculate vertebral inclination angles and derive consecutive CAs. Additional spinal parameters, including coronal balance (T1PL-CSVL), force line (FL), and FL balance, were computed to enable comprehensive spinal evaluation.Main results. The proposed method achieved a vertebral segmentation Dice coefficient of 94.7%. The mean absolute error of the CA was, outperforming the minimum bounding rectangle method () and novice manual measurements (), with an intraclass correlation coefficient of 0.958. In diagnostic grading, 120 out of 142 patients were correctly classified (84.5% success rate). Longitudinal follow-up demonstrated accurate tracking of structural improvements and coronal balance recovery following conservative treatment.Significance. This approach enables automatic, precise, and comprehensive scoliosis evaluation by integrating fine-grained segmentation with geometric modeling of spinal curvature. The proposed method improves spinal assessment accuracy and facilitates longitudinal scoliosis monitoring, offering substantial clinical utility and impact in computer-aided orthopedic diagnosis.