Lung nodule classification combining rule-based and SVM

Abstract

In order to classify lung nodules, an approach combining rule-based and SVM is proposed in the paper. Firstly, the candidate ROIs shape features are calculated, and some blood vessels are get rid of using rule-based according to shape features; secondly, the remainder candidates gray and texture features are calculated; finally, the shape, gray and texture features are taken as the inputs of the SVM (Support Vector Machine) classifier to classify the candidates. Experimental results show that the rule-based approach has no omission, but the misclassification probability is too large; the approach combining rule-based and SVM has higher omission than SVM, but lower misclassification. The causes of nodules omission and misclassification are summarized and the solution is discussed in the paper at last.