Diagnosis of lung nodule using semivariogram and geometric measures in computerized tomography images

This paper uses the geostatistical function - semivariogram and a set of 3D geometric measures - sphericity index, convexity index, extrinsic and intrinsic curvature index and surface type, to characterize 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 techniques for classification and analysis (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.