Paper
21 March 1989 An Application Of The Blackboard Architecture To Left Ventricular Boundary Detection
Saeid Tehrani, Terry E. Weymouth, G. B. John Mancini
Author Affiliations +
Abstract
Interpretation of X-ray motion pictures of the heart (cineventiculograms of the left ventricle) is complicated by the low contrast of the images and the elastic motion of the heart. We describe a framework for the application of knowledge in the form of diagnostically relevant models of the heart in motion to the problem of placing the heart boundary in each frame of the motion sequence. We employ a blackboard architecture [Nii 86;Weymouth 87] as a basis for the image interpretation. In this framework, local features, such as edges, are grouped to build a complete description of the moving heart. The knowledge is organized in a hierarchy with Knowledge sources (KS's) operating on different levels of the hierarchy. Opportunistic problem-solving techniques are used to control the order of activation of both data-directed and goal-driven KS's.
© (1989) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Saeid Tehrani, Terry E. Weymouth, and G. B. John Mancini "An Application Of The Blackboard Architecture To Left Ventricular Boundary Detection", Proc. SPIE 1095, Applications of Artificial Intelligence VII, (21 March 1989); https://doi.org/10.1117/12.969299
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Cited by 1 scholarly publication.
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KEYWORDS
Heart

Image segmentation

Motion models

Artificial intelligence

Statistical modeling

Motion analysis

Data modeling

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