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.
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Silva, A.C., Paiva, A.C., Carvalho, P.C.P., Gattass, M. (2005). Semivariogram and SGLDM Methods Comparison for the Diagnosis of Solitary Lung Nodule. In: Marques, J.S., Pérez de la Blanca, N., Pina, P. (eds) Pattern Recognition and Image Analysis. IbPRIA 2005. Lecture Notes in Computer Science, vol 3523. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11492542_59
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DOI: https://doi.org/10.1007/11492542_59
Publisher Name: Springer, Berlin, Heidelberg
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