ANGY: A Rule-Based Expert System for Identifying and Isolating Coronary Vessels in Digital Angiograms
Document Type Technical Report
University of Pennsylvania Department of Computer and Information Science Technical Report No. MS-CIS-84-63.
This thesis details the design and implementation of ANGY, a Rule-based Expert System in the domain of medical image processing. Given a subtracted digital angiogram of the chest, ANGY identifies and isolates the coronary vessels, while ignoring any non-vessel structures which may have arisen from noise, variations in background contrast, imperfect subtraction, and non-relevant anatomical detail. The over all system is modularized into three stages: The preprocessing stage and the two stages embodied in the expert itself. In the preprocessing stage, low level image processing routines written in C are used to create a segmented representation of the input image. These routines are applied sequentially. The expert system is rule-based and is written in OPS5 and LISP. It is separated into two independent stages: The low level image processing stage embodies a domain independent knowledge of segmentation, grouping, and shape analysis. Working with both edges and regions, it determines such relations as parallel and adjacent and attempts to refine the segmentation begun by the preprocessing. The high level medical stage embodies a domain dependent knowledge of coronary physiology and anatomy. Applying this knowledge to the objects and relations determined in the preceeding two stages, it identifies those objects which are vessels and eliminates all others.
Date Posted: 15 November 2007