Title: Lung cancer diagnosis and staging using firefly algorithm fuzzy C-means segmentation and support vector machine classification of lung nodules

Authors: M. Lavanya; P. Muthu Kannan; M. Arivalagan

Addresses: Department of Electrical and Electronics Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Thandalam, Chennai, India ' Department of Electrical and Electronics Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Thandalam, Chennai, India ' Department of Electronics and Instrumentation Engineering, Saveetha Engineering College, Thandalam, Chennai, India

Abstract: Lung nodule segmentation is an important division of automated disease screening systems in cancer identification. The morphological variations of lung nodules correspond to chances of cancer. The incorrect detection of these lung nodules because of misclassification leads to false results and incorrect strategies of diagnosis. This misclassification also misdirects pharmaceutical experts for wrong preparation of drugs for diagnosis. There are different methods that are available for detection but there is always a space for improvement in terms of various parameters for better results. Therefore in this work image enhancement is done by histogram equalisation and further noise removal is carried over by anisotropic diffusion filter. The nodule segmentation process is carried over by firefly algorithm fuzzy C-means (FA-FCM) segmentation process. Finally, after feature extraction is done classification of lung cancer staging is carried out using support vector machine (SVM) classifier. Therefore, the nodule is accurately detected considering the morphological changes that are noted for the results which lead to proper medicine preparation and accurate diagnosis of lung nodules.

Keywords: lung nodule; histogram equalisation; anisotropic filter; segmentation; firefly algorithm fuzzy C-means; FA-FCM; support vector machine; SVM.

DOI: 10.1504/IJBET.2021.119504

International Journal of Biomedical Engineering and Technology, 2021 Vol.37 No.2, pp.185 - 200

Received: 06 Jul 2018
Accepted: 21 Sep 2018
Published online: 08 Dec 2021 *

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