  Lung cancer begins in the lungs and leading to the reason of cancer demise
amid population in the creation. According to the American Cancer Society,
which estimates about 27% of the deaths because of cancer. In the early phase
of its evolution, lung cancer does not cause any symptoms usually. Many of the
patients have been diagnosed in a developed phase where symptoms become more
prominent, that results in poor curative treatment and high mortality rate.
Computer Aided Detection systems are used to achieve greater accuracies for the
lung cancer diagnosis. In this research exertion, we proposed a novel
methodology for lung Segmentation on the basis of Fuzzy C-Means Clustering,
Adaptive Thresholding, and Segmentation of Active Contour Model. The
experimental results are analysed and presented.
