An Efficient Decision Support System for Diagnosing Brain Tumor Images

The objective of this work is to develop and implement a computer-aided decision support system for an automated diagnosis and classification of CT-scan brain images. In this paper, we propose a method based on fuzzy Support Vector Machine to enhance the diagnosis of CT-scan brain images. The proposed method uses ReFe_SeDi (Relevant Feature Selection and Discretization) algorithm that performs feature selection and discretization process. The experimental results of our approach show better performance than the traditional methods multilayer back propagation network and SVM. Such fuzzy-SVM system with feature extraction and selection algorithm helps in developing a computer-aided diagnosis system for CT-scan brain images and can be used as a secondary observer in clinical decision making.

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