Semivariogram and SGLDM methods comparison for the diagnosis of solitary lung nodule

Authors:
Aristófanes C. Silva;Anselmo C. Paiva;Paulo C. P. Carvalho;Marcelo Gattass
Affiliations:
Federal University of Maranhão – UFMA, São Luís, MA, Brazil;Federal University of Maranhão – UFMA, São Luís, MA, Brazil;Institute of Pure and Applied Mathematics – IMPA, Rio de Janeiro, RJ, Brazil;Pontifical Catholic University of Rio de Janeiro – PUC-Rio, Rio de Janeiro, RJ, Brazil
Venue:
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part II
Year:
2005

Citing 2
Cited 2

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Abstract

The present work seeks to develop a computational tool to suggest the malignancy or benignity of Solitary Lung Nodules by means of analyzing texture measures obtained from computerized tomography images.Two methods are proposed, that analyze the nodules' texture by means of the Spatial Gray Level Dependence Method and a geostatistical function denominated semivariogram. A sample with 36 nodules, 29 benign and 7 malignant, was analyzed and the preliminary results of these methods are very promising in characterizing lung nodules. The obtained results suggested that the proposed methods have great potential in the discrimination and classification of Solitary Lung Nodules.