One of the main sources of fatalities in the world is lung cancer. Lung cancer is responsible for 7.6 million deaths worldwide each year, as per the statistics of World Health Organization (WHO). It is only possible to treat lung cancer when it is identified at an early stage. Lung cancer may be diagnosed using a variety of technologies, including isotope, MRI, CT, as well as X-ray. CT scan images are not easy to understand, but using CNN with Image Segmentation is a straightforward approach to detect Lung cancer. CNN (Convolutional Neural Network) is a deep structured technique that has been extensively used to investigate the potential to extract and visualize hidden texture information from image datasets. The objective of the examination is to consequently extricate self-learned components with a start to finish learning CNN and contrast the discoveries with the presentation of standard best in class and customary PC helped indicative frameworks.