A classification and analysis of pulmonary nodules in CT images using random forest

The main aim of this work is to propose a novel Computer-aided detection (CAD) system based on a Contextual clustering combined with region growing for assisting radiologists in early identification of lung cancer from computed tomography(CT) scans. Instead of using conventional thresholding approach, this proposed work uses Contextual Clustering which yields a more accurate segmentation of the lungs from the chest volume. Following segmentation GLCM and LBP features are extracted which are then classified using three different classifiers namely Random forest, SVM and k-NN.