Research Article Open Access

AN EFFECTIVE CLASSIFICATION OF BENIGN AND MALIGNANT NODULES USING SUPPORT VECTOR MACHINE

Abstract

Support Vector Machine (SVM) is a machine learning technique that trains the system with the known data; it analyzes and identifies the patterns. SVM can be used for classifying the medical data because of its simplicity. Real time lung images are taken for the study. Lung images are segmented to retrieve the region of interest and these regions or nodules are used for classification. Proper threshold values are decided for each feature and classification rules are framed. Then these rules are passed to the SVM classifier. In this paper, classifications of benign and malignant nodules are done using different SVM kernels and their performance measures are compared.

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