# VERIDAH

Automatic vertebra labeling has long assumed twelve thoracic and five lumbar vertebrae, so a spine with one extra or one missing segment shifts every label. VERIDAH feeds per-vertebra classification outputs into an anatomy-constrained sequence solver that picks the most consistent label sequence at any field of view. Across 1000 T2w sagittal MRI and 365 CT images, all vertebrae were labeled correctly in 98.30% and 99.18% of subjects, versus 94.24% and 77.26% for comparison methods; thoracic and lumbar enumeration anomalies were identified in 87.80% and 94.48% of MRI cases and 96.30% and 97.22% of CT cases.

Automatic vertebra labeling has long assumed twelve thoracic and five lumbar vertebrae, so a spine with one extra or one missing segment shifts every label. VERIDAH feeds per-vertebra classification outputs into an anatomy-constrained sequence solver that picks the most consistent label sequence at any field of view. Across 1000 T2w sagittal MRI and 365 CT images, all vertebrae were labeled correctly in 98.30% and 99.18% of subjects, versus 94.24% and 77.26% for comparison methods; thoracic and lumbar enumeration anomalies were identified in 87.80% and 94.48% of MRI cases and 96.30% and 97.22% of CT cases.