Fully Automatic Segmentation of Coronary Vessel Structures in Poor Quality X-Ray Angiogram Images
In this paper a fully automatic method is presented for extracting blood vessel structures in poor quality coronary angiograms. The method extracts blood vessels by exploiting the spatial coherence in the image. Accurate sampling of a blood vessel requires a background elimination technique. A circular sampling technique is employed to exploit the coherence. This circular sampling technique is also applied to determine the distribution of intersection lengths between the circles and blood vessels at various threshold depths. After this sampling process, disconnected parts to the centered object are eliminated, and then the distribution of the intersection length is examined to make the decision about whether the point is on the blood vessel. To produce the final segmented image, mis-segmented noisy parts and discontinuous parts are eliminated by using angle couples and circular filtering techniques. The performance of the method is examined on various poor quality X-ray angiogram images.
KeywordsMedical Image Automatic Segmentation Intersection Length Vessel Structure Current Pixel
Unable to display preview. Download preview PDF.
- 8.Kirbas, C., Francis, K., Queck, H.: A review of vessel extraction Techniques and Algorithms. Vision Interfaces and Systems Laboratory, Department of Computer Science and Engineering, Wright State University, Dayton Ohio (2002)Google Scholar
- 9.Suri, J.S., Liu, K.C., Reden, L., Laxminarayan, S.: A review on MR vascular image processing: Skeleton versus nonskeleton approaches. IEEE Transaction on Information Technology in Biomedicine 6 (2002)Google Scholar
- 10.Kottke, D.P., Sun, Y.: Adaptive segmentation of coronary angiograms. In: Proc. 14th Northeast Bioeng. Conf., pp. 278–290 (1988)Google Scholar
- 12.Francis, K., Quek, H., Kirbas, C.: Vessel extraction in medical images by wave-propagation and trace-back. IEEE Transaction on Medical Imaging 20 (2001)Google Scholar
- 14.Osher, S., Sethian, J.A.: Fronts propagating with curvature dependent speed: Algorithms based on Hamilton Jacobi formulation. Journal of Computational Physics 79 (1988)Google Scholar
- 15.Yanagihara, Y., Sugahara, T., Sugimoto, N.: Extraction of vessel in brain using fast x-ray CT images. Systems and Computers in Japan 25, 78–85 (1994)Google Scholar