Published Paper Details:

Cancer is an extensive global and universal disease nowadays which pretends to be the utmost cause for a large impermanence rate among men and women every era. Approximately 80-85% of the people who get affected by cancer are being succumbed to death. Recognition of cancer at the first stage is the only aspect in front of us to give proper treatment. Among numerous types of cancers, lung cancer is a very fearful and complicated one. Lung cancer means the growth of tumor cells briskly and having chances of spreading those cancer cells to other organs which in turn damaging other normal tissue cells of the body. Noticing tumor prematurely can help to cure the disease completely and it becomes pivotal to find out whether the tumor has been changed to cancer or not, if the prognostication is made at an initial stage, then countless lives that are at risk could be rescued and accurate prediction can help the doctors to start their treatment at the earliest. In this paper, we have proposed a simple, easy, and precise method for accurate prediction of the stage of cancer using CT images of the lungs in Image processing. For this process, a CT image will be considered, and then the image will be pre-processed for noise removal. Further segmentation is done to identify and separate desired tumor nodule and extraction of morphological features such as area, perimeter, eccentricity, and diameter is carried out under feature extraction. Finally, the classification of lung cancer into different stages based on the size of tumor results has been proposed using MATLAB which is more accurate and less time-consuming when compared to other lung cancer prediction systems. The method proposed in this paper to detect a tumor in the lungs is simpler when compared to applying other difficult algorithms.