Abstract
In this paper, a set of three features for aiding classification of lung nodule bearing candidates based upon morphological characteristics is proposed. Metrics were validated using Support Vector Machine (SVM) technique as classifier. Preliminary results indicate the efficiency of the adopted measurements, taking into account the sensitivity and specificity high rates obtained from the studied samplings. © Springer-Verlag Berlin Heidelberg 2007.
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Da Silva Sousa, J. R. F., Silva, A. C., & De Paiva, A. C. (2007). Lung structure classification using 3D geometric measurements and SVM. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4756 LNCS, pp. 783–792). Springer Verlag. https://doi.org/10.1007/978-3-540-76725-1_81
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