P. S. Ramapraba1,*, P. Epsiba2, K. Umapathy3, E. Sivanantham4
Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2177-2189, 2023, DOI:10.32604/iasc.2023.032040
Abstract The classification of lung nodules is a challenging problem as the visual analysis of the nodules and non-nodules revealed homogenous textural patterns. In this work, an Auxiliary Classifier (AC)-Generative Adversarial Network (GAN) based Lung Cancer Classification (LCC) system is developed. The proposed AC-GAN-LCC system consists of three modules; preprocessing, Lungs Region Detection (LRD), and AC-GAN classification. A Wiener filter is employed in the preprocessing module to remove the Gaussian noise. In the LRD module, only the lung regions (left and right lungs) are detected using iterative thresholding and morphological operations. In order to extract the lung region only, flood filling… More >
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