A rule-based approach to stroke lesion analysis from CT brain images

Abstract

This paper presents a method for automatic segmentation and labeling of computerised tomography (CT) head images of stroke lesions. The method is composed of three steps. The first step is automatic determination of head symmetry axis, with the possibility of manual improvement of the result if necessary. Symmetry axis calculation is based on moments. In the second step, the seeded region-growing (SRG) algorithm is used to segment the input image into a number of regions having uniform brightness. Features of these regions, such as brightness, area, neighborhood and relative position to the symmetry axis are used to create facts for a rule-based expert system. Based on created facts and pre-defined rules as input, the rule-based expert system is used in the third step to label regions as background, skull, gray/white matter, CSF and stroke. Experimental results have been conducted and have demonstrated the feasibility and accuracy of the proposed method.

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