Visualizing the spine using anatomical knowledge

In vivo anatomy is now routinely displayed as 2-D and 3-D images obtained from Computed X-ray Tomograpy (CT), Magnetic Resonance Imaging (MRI), and other diagnostic modalities. Most current medical visualization methods rely on pixel intensities to segment the data into tissues. However, structural features must be differentiated by a human operator, and geometric measurements of the anatomy are tedious and error prone to compute. This paper describes processing and imaging methods to aid the interpretation of CT studies of the spine. These procedures incorporate knowledge of the symmetry, shapes, and spatial relationships of vertebrae to locate the spinal cord and major components of vertebral bone from CT slices of the spine and automatically compute anatomical measurements. Results of these methods are shown as applied to the cervical (neck) and lumbar (lower back) regions of the spine.