Diagnosis of lung nodule using Gini coefficient and skeletonization in computerized tomography images

This paper uses the Gini coefficient and a set of skeleton measures, with the purposes, with the purpose of characterizing lung nodules as malignant or benign in computerized tomography images.Based on a sample of 31 nodules, 25 benign and 6 malignant, these methods are first analyzed individually and then jointly, with classfication and analysis techniques (linear stepwise discriminant analysis, leave-one-out and ROC curve). We have concluded that the individual measures and their combinations produce good results in the diagnosis of lung nodules.

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