Lung Nodules Classification in CT Images Using Simpson's Index, Geometrical Measures and One-Class SVM

Authors:
Cleriston Araujo Silva;Aristófanes Corrêa Silva;Stelmo Magalhães Netto;Anselmo Cardoso Paiva;Geraldo Braz Junior;Rodolfo Acatauassú Nunes
Affiliations:
Federal University of Maranhão - UFMA, São Luís, Brazil 65085-580;Federal University of Maranhão - UFMA, São Luís, Brazil 65085-580;Federal University of Maranhão - UFMA, São Luís, Brazil 65085-580;Federal University of Maranhão - UFMA, São Luís, Brazil 65085-580;Federal University of Maranhão - UFMA, São Luís, Brazil 65085-580;State University of Rio de Janeiro - UERJ, São Francisco de Xavier, Rio de Janeiro, Brazil 20550-900
Venue:
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
Year:
2009

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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%.