Lung diseases are a major concern nowadays. The human body consists of diverse fundamental organs, out of which Lung is one of them. The Lungs are made up of two sections, right lung and left lung and the main function of lungs is to facilitate exchange of gas which is called as breathing or respiration. Our present modern lifestyle, ecological contamination, adulteration is helping in expanding the Human Lungs issue. What's more, simultaneously there are various Image processing techniques that are blending the tremendous answer for the medical field to identify and analyze the Lung's illnesses. A system development which is based on Deep learning is proposed to get better and accurate result which includes Image Processing techniques like image pre-processing, segmentation, thresholding, image enhancement and classification. Computer Tomography (CT) scan images takes from LIDC database as an input to examine the Lungs disorders in human body. Convolution Neural Network is practiced to perform classification of input lung images into cancerous and noncancerous classes. This technique will assist to oncologists as second opinion and will develop the accurate quality of lung cancer detection. With the proposed system, lung cancer detection is done with 98.44% of accuracy. © 2022 IEEE.