Lung cancer segmentation in CT images using Fuzzy-C means clustering and artificial bee colony algorithm

Abstract

One of the challenging issues to most of the researches is to segment pulmonary nodules from the CT Lung images. This Research focus on rapid segmentation of pulmonary nodules from the CT Lung images based on Fuzzy-C Means Clustering and Artificial Bee Colony Algorithm. Classic 2D otsu algorithm is used for segmentation and Artificial Bee colony algorithm is used for finding optimum threshold values. Finally, FCM (Fuzzy-C Means) clustering is used over the CT segmented images to cluster the images.