Rule-based automatic segmentation for 3D coronary arteriography

Alok Sarwal; Paul Truitt; Fusun Ozguner; Qian Zhang; Dennis L. Parker

doi:10.1117/12.58597

1 March 1992 Rule-based automatic segmentation for 3-D coronary arteriography

Alok Sarwal, Paul Truitt, Fusun Ozguner, Qian Zhang, Dennis L. Parker

Proceedings Volume 1708, Applications of Artificial Intelligence X: Machine Vision and Robotics; (1992) https://doi.org/10.1117/12.58597
Event: Aerospace Sensing, 1992, Orlando, FL, United States

Abstract

Coronary arteriography is a technique used for evaluating the state of coronary arteries and assessing the need for bypass surgery and angioplasty. The present clinical application of this technology is based on the use of a contrast medium for manual radiographic visualization. This method is inaccurate due to varying interpretation of the visual results. Coronary arteriography based quantitations are impractical in a clinical setting without the use of automatic techniques applied to the 3-D reconstruction of the arterial tree. Such a system will provide an easily reproducible method for following the temporal changes in coronary morphology. The labeling of the arteries and establishing of the correspondence between multiple views is necessary for all subsequent processing required for 3-D reconstruction. This work represents a rule based expert system utilized for automatic labeling and segmentation of the arterial branches across multiple views. X-ray data of two and three views of human subjects and a pig arterial cast have been used for this research.

Citation Download Citation

Alok Sarwal, Paul Truitt, Fusun Ozguner, Qian Zhang, and Dennis L. Parker "Rule-based automatic segmentation for 3-D coronary arteriography", Proc. SPIE 1708, Applications of Artificial Intelligence X: Machine Vision and Robotics, (1 March 1992); https://doi.org/10.1117/12.58597

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