Knowledge-based system for the fully automatic quantification of coronary stenotic lesions from two angiographic projections

D. Delaere; Luc C.F. Maes; Carl Smets; Paul Suetens; Andre J. Oosterlinck; Frans Van de Werf

doi:10.1117/12.18911

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1 July 1990 Knowledge-based system for the fully automatic quantification of coronary stenotic lesions from two angiographic projections

D. Delaere, Luc C.F. Maes, Carl Smets, Paul Suetens, Andre J. Oosterlinck, Frans Van de Werf

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Proceedings Volume 1233, Medical Imaging IV: Image Processing; (1990) https://doi.org/10.1117/12.18911
Event: Medical Imaging '90, 1990, Newport Beach, CA, United States

Abstract

In this paper we describe work-in-progress regarding a fully automatic reporting system for coronary artery stenotic lesions. In a first step all blood vessel segments are assigned their anatomical label according to a coronary anatomy model. Segment labeling is done using a constraint satisfaction technique because most anatomical coronary artery knowledge can be formulated as umary constraints only depending on local segment attributes and binary relational constraints such as thicker than left ofand above. In a second step we perform an automatic quantification of all artery trajectories. Therefore we calculate a stenosis severity score for each segment which is not only based on local properties like per cent diameter or per cent area stenosis but also takes into account the anatomical significance of the vessel. For example a stenotic lesion proximal on the Left Anterior Descending (LAD) branch is much more significant than one on its distal side branches. Results are presented on clinical coronary angiograms. 1.

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D. Delaere, Luc C.F. Maes, Carl Smets, Paul Suetens, Andre J. Oosterlinck, and Frans Van de Werf "Knowledge-based system for the fully automatic quantification of coronary stenotic lesions from two angiographic projections", Proc. SPIE 1233, Medical Imaging IV: Image Processing, (1 July 1990); https://doi.org/10.1117/12.18911

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