24 March 2016 Classification of pulmonary nodules in lung CT images using shape and texture features
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Abstract
Differentiation of malignant and benign pulmonary nodules is important for prognosis of lung cancer. In this paper, benign and malignant nodules are classified using support vector machine. Several shape-based and texture-based features are used to represent the pulmonary nodules in the feature space. A semi-automated technique is used for nodule segmentation. Relevant features are selected for efficient representation of nodules in the feature space. The proposed scheme and the competing technique are evaluated on a data set of 542 nodules of Lung Image Database Consortium and Image Database Resource Initiative. The nodules with composite rank of malignancy “1",”2" are considered as benign and “4",”5" are considered as malignant. Area under the receiver operating characteristics curve is 0:9465 for the proposed method. The proposed method outperforms the competing technique.
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Ashis Kumar Dhara, Ashis Kumar Dhara, Sudipta Mukhopadhyay, Sudipta Mukhopadhyay, Anirvan Dutta, Anirvan Dutta, Mandeep Garg, Mandeep Garg, Niranjan Khandelwal, Niranjan Khandelwal, Prafulla Kumar, Prafulla Kumar, "Classification of pulmonary nodules in lung CT images using shape and texture features", Proc. SPIE 9785, Medical Imaging 2016: Computer-Aided Diagnosis, 97852Y (24 March 2016); doi: 10.1117/12.2214466; https://doi.org/10.1117/12.2214466
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