21st Signal Processing and Communications Applications Conference (SIU), CYPRUS, 24 - 26 April 2013
Recognition of lung nodules and classification of them as benign and malignent are very important in diagnosis of lung cancer. Present methods on nodule classification generally concentrate on defining nodule as either benign or malignent but do not consider radiographic descriptors that play important role on classification of small-sized lung nodules. In this paper, features extracted from nodule images to denote radiographic descriptors are studied. With the results from classification and dimension reduction approaches, which images features truly denote radiographic descriptors is analyzed.