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International Journal of Soft Computing
Year: 2009  |  Volume: 4  |  Issue: 4  |  Page No.: 157 - 161

Segmentation of Computed Tomography Brain Images Using Genetic Algorithm

R. Ganesan and S. Radhakrishnan    

Abstract: Unlike research on brain segmentation of Magnetic Resonance Imaging (MRI) data, research on Computed Tomography (CT) brain segmentation is relatively scarce. We have begun to explore methods for soft tissue segmentation of CT brain data with a goal of enhancing the utility of CT for brain imaging. In this study, a novel method for automatic segmentation of Computed Tomography (CT) brain images has been presented. The method consists of two major phases. In the first phase, the original images are enhanced by using Selective Median Filter (SMF) and in the second phase the Genetic Algorithm (GA) is used to segment the image. The proposed method has been applied to real patient CT images and the performance is evaluated using Receiver Operating Characteristic (ROC) curve analysis. The result shows the superior performance of the proposed algorithm.

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