This paper uses the Gini coefficient and a set of skeleton measures, 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 classification 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.