Lumbar spine visualisation based on kinematic analysis from videofluoroscopic imaging.
Low back pain is a significant problem and its cost is enormous to society. However, diagnosis of the underlying causes remains problematic despite extensive study. Reasons for this arise from the deep-rooted situation of the spine and also from its structural complexity. Clinicians have to mentally convert 2-D image information into a 3-D form to gain a better understanding of structural integrity. Therefore, visualisation and animation may be helpful for understanding, diagnosis and for guiding therapy. Some low back pain originates from mechanical disorders, and study of the spine kinematics may provide an insight into the source of the problem. Digital videofluoroscopy was used in this study to provide 2-D image sequences of the spine in motion, but the images often suffer due to noise, exacerbated by the very low radiation dosage. Thus determining vertebrae position within the image sequence presents a considerable challenge. This paper describes a combination of spine kinematic measurements with a solid model of the human lumbar spine for visualisation of spine motion. Since determination of the spine kinematics provides the foundation and vertebral extraction is at the core, this is discussed in detail. Edge detection is a key feature of segmentation and it is shown that phase congruency performs better than most established methods with the rather low-grade image sequences from fluoroscopy. The Hough transform is then applied to determine the positions of vertebrae in each frame of a motion sequence. In the Hough transform, Fourier descriptors are used to represent the vertebral shapes. The results show that the Hough transform is a very promising technique for vertebral extraction from videofluoroscopic images. A dynamic visualisation package has been developed in order to view the moving lumbar spine from any angle and viewpoint. Wire frame models of the vertebrae were built by using CT images from the Visible Human Project and these models are scaled to match the fluoroscopic image data. For animation, the spinal kinematic data from the motion study is incorporated.
Zheng
Y
Y
Department of Electronics and Computer Science, University of Southampton, SO17 1BJ, UK. yz99r@ecs.soton.ac.uk
Nixon
M S
MS
Allen
R
R
D000465:Algorithms; D003198:Computer Simulation; D005471:Fluoroscopy / Q000379:methods*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008159:Lumbar Vertebrae / Q000000981:diagnostic imaging* / Q000502:physiology; D008954:Models, Biological; D009068:Movement / Q000502:physiology; D010363:Pattern Recognition, Automated; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D014741:Video Recording / Q000379:methods