Automated segmentation of lumbar vertebrae in digital videofluoroscopic images

Low back pain is a significant problem in the industrialized world. Diagnosis of the underlying causes can be extremely difficult. Since mechanical factors often play an important role, it can be helpful to study the motion of the spine. Digital videofluoroscopy has been developed for this study and it can provide image sequences with many frames, but which often suffer due to noise, exacerbated by the very low radiation dosage. Thus, determining vertebra position within the image sequence presents a considerable challenge. There have been many studies on vertebral image extraction, but problems of repeatability, occlusion and out-of-plane motion persist. In this paper, we show how the Hough transform (HT) can be used to solve these problems. Here, Fourier descriptors were used to describe the vertebral body shape. This description was incorporated within our HT algorithm from which we can obtain affine transform parameters, i.e., scale, rotation and center position. The method has been applied to images of a calibration model and to images from two sequences of moving human lumbar spines. The results show promise and potential for object extraction from poor quality images and that models of spinal movement can indeed be derived for clinical application.