Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7693
Title: Object-oriented knowledge-based system for image diagnosis
Authors: Chan, Samuel W. K. 
Prof. LEUNG Kwong Sak 
Wong, W. S. Felix 
Issue Date: 1996
Source: Applied Artificial Intelligence, 1996, vol.10 (5), pp. 407 - 438
Journal: Applied Artificial Intelligence 
Abstract: In this article the design and implementation of a high-level image diagnosis system are described. A knowledge-based system, OOI, has been developed to incorporate the image processing abilities. It employs a robust control strategy in the object-oriented approach that minimizes the amount of domain-specific control knowledge. Knowledge objects are constructed that embed specialized methods or metaknowledge in image processing. They work independently of each other. The highly modular architecture allows the knowledge engineers to modify the knowledge without worrying about any unexpected side effects. Reasoning in OOI proceeds in both top-down and in bottom-up schemes. The system has been tested in medical image analysis. Cancer cell lesion classification is used as an application domain to illustrate how image diagnosis can be implemented in our system. Results attest to the efficacy of this framework in both image recognition and diagnosis. © 1996 Taylor & Francis Group, LLC.
Type: Peer Reviewed Journal Article
URI: http://hdl.handle.net/20.500.11861/7693
ISSN: 08839514
DOI: 10.1080/088395196118489
Appears in Collections:Applied Data Science - Publication

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