Abstract
The growing appreciation of the pathophysiological and prognostic importance of arterial morphology has led to the realization that angiograms are inherently limited in defining the distribution and extension of coronary wall disease. By Intravascular Ultrasound images physicians have a picture of the composition of vessel in detail. However, observing an intravascular ultrasound stack of images, it is difficult to figure out the image position and extension with regard to the vessel parts and ramifications, and misclassification or misdiagnosis of lesions is possible. The objective of this work is to develop a computer vision technique to fuse the information from angiograms and intravascular ultrasound images defining the correspondence of every ultrasound image with a corresponding point of the vessel in the angiograms.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
J.J. Gerbrands A.C.M. Dumay, J.H.C. Reiber. Determination of optimal angiographic viewing angles: Basis principles and evaluation study. IEEE Medical Imaging, 13:13–23, 1994.
American Heart Association. 2001 heart and stroke statistical update. 2000. Dallas, Texas: American Heart Association, http://www.americanheart.org/.
J.C. Beatty B.A. Barsky, R.H. Bartels. An Introduction to Splines for use in Computer Graphics and Geometry Modeling. Morgan Kaufmann Publishers INC, 1987.
C. Von Birgelen, C. Slager, C. Di Mario, P.J. de Feyter, and W. Serruys. Volumetric intracoronary ultrasound a new maximum progression-regression of atherosclerosis. Atherosclerosis 118 Suppl, 1995.
Laurent D. Cohen and Ron Kimmel. Global minimum for active contour models: A minimal path approach. International Journal of Computer Vision, 24(1):57–78, August 1997.
P. Kearney, I. Starkey, and G. Sutherland. Intracoronary ultrasound: Current state of the art. British Heart Journal (Supplement 2), 73:16–25, 1995.
M. Sonka, X. Zhang, M. Siebes, and M. Bissing. Segmentation of intravascular ultrasound images: A knowledge-based approach. IEEE Transactions on Medical Imaging, 14:719–732, 1995.
X. Zhang, C.R. McKay, and M. Sonka. Image segmentation and tissue characterization in intravascular ultrasound. IEEE Medical Imaging, 17:880–899, 1998.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rotger, D., Radeva, P., Mauri, J., Fernandez-Nofrerias, E. (2002). Internal and External Coronary Vessel Images Registration. In: Escrig, M.T., Toledo, F., Golobardes, E. (eds) Topics in Artificial Intelligence. CCIA 2002. Lecture Notes in Computer Science(), vol 2504. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36079-4_36
Download citation
DOI: https://doi.org/10.1007/3-540-36079-4_36
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-00011-2
Online ISBN: 978-3-540-36079-7
eBook Packages: Springer Book Archive