Automated 3D Segmentation of Vertebral Bodies and Intervertebral Discs from MRI

Recent developments in high resolution MRI scanning of the human spine are providing increasing opportunities for the development of accurate automated approaches for pathoanatomical assessment of intervertebral discs and vertebrae. We are developing a fully automated 3D segmentation approach for MRI scans of the human spine based on statistical shape analysis and template matching of grey level intensity profiles. The algorithm reported in the present study was validated on a dataset of high resolution volumetric scans of lower thoracic and lumbar spine obtained on a 3T scanner using the relatively new 3D SPACE (T2-weighted) pulse sequence, and on a dataset of axial T1-weighted scans of lumbar spine obtained on a 1.5T system. A 3D spine curve is initially extracted and used to position the statistical shape models for final segmentation. Initial validating experiments show promising results on both MRI datasets.