Lung nodules classification in CT images using simpson's index, geometrical measures and one-class SVM

Abstract

In this paper, we present the Simpson's Index, a feature used in Spatial Analysis and in Biology, specifically in Ecology to determine the homogeneity or heterogeneity of a certain species. This index will be investigated as a promising feature, since little observation has been done on the application of these features for the analysis of medical images, with three geometrical features, in the characterization of lung nodules as benign or malignant. Using One-Class SVM for classification we obtained sensibility rates of 100%, specificity 100% and accuracy of 100%. © 2009 Springer Berlin Heidelberg.