Application of TVD-Net for sagittal alignment and instability measurements in cervical spine radiographs.

This study presents a novel and efficient deep-learning model to assist landmarks identification and angulation and displacement calculation on lateral cervical spine radiographs, and demonstrates excellent accuracy in measuring cervical alignment and sound sensitivity and specificity in cervical instability diagnosis. It should be helpful for future research and clinical applications.