Computer Vision in Osteoporotic Vertebral Fracture Risk Prediction: A Systematic Review

Abstract

Osteoporotic vertebral fractures (OVFs) are a significant health concern linked to increased morbidity, mortality, and diminished quality of life. Traditional OVF risk assessment tools like bone mineral density (BMD) only capture a fraction of the risk profile. Artificial intelli-gence, specifically computer vision, has revolutionized other fields of medicine through analysis of videos, histopathology slides and radiological scans. In this review, we provide an overview of computer vision algorithms and current computer vision models used in predicting OVF risk. We highlight the clinical applications, future directions and limitations of computer vision in OVF risk prediction.