Lung cancer detection system using lung CT image processing

Cancer is the root cause for a large number of deaths worldwide, out of which lung cancer is the cause of the highest mortality rates. Computer tomography scan is employed by radiologists to detect cancer in the body and track its growth. Visual interpretation of database can lead to cancer detection at later stages, thus leading to late treatment of cancer which only boosts up the cancer death rates. Therefore, image processing tools can be used for early detection of cancer. In this paper, a lung cancer detection algorithm is proposed using mathematical morphological operations for segmentation of the lung region of interest, from which Haralick features are extracted and used for classification of cancer by artificial neural networks.