Volume-based inter difference XOR pattern: a new pattern for pulmonary nodule detection in CT images

Abstract

The pulmonary nodule identification which paves the path to the cancer diagnosis is a challenging task today. The proposed work, volume-based inter difference XOR pattern (VIDXP) provides an efficient lung nodule detection system using a 3D texture-based pattern which is formed by XOR pattern calculation of inter-frame grey value differences among centre frame with its neighbourhood frames in rotationally clockwise direction, for every segmented nodule. Different classifiers such as random forest (RF), decision tree (DT) and AdaBoost are used with ten trails of five-fold cross validation test for classification. The experimental analysis in the public database, lung image database consortium-image database resource initiative (LIDC-IDRI) shows that proposed scheme gives better accuracy while comparing with existing approaches. Further, the proposed scheme is enhanced by combining shape information using histogram of oriented gradient (HOG) which improves the classification accuracy.