The number of people who have lung cancer is expected to increase. Five million men and women are affected by it annually. The 3D CT scan pictures are used to determine the degree of lung cancer. To localize cancerous lung nodules, this study used a deep learning technique. The proposed technique employs the most effective lung cancer classification framework using deep learning to classify lung CT images into malignant, benign, and normal lung nodules.the proposed frame work of lung cancer prediction of classification of malignant and benign lung cancer CT images using deep learning techniques as obtained from real time data sets undergoes following steps like pre-processing steps with resizing the image(512*512) and conversion of color to gray,followed by removing noise with median filter and then thresholding. Next step is the lung region segmentation with CNN architectureand it is classified as malignant and benign lung cancer.The algorithm detects lung malignancies on chest X-rays with pre-processing and lung region segmentation algorithm and labels them using the proposed deep learning framework with the machine learning techniques for the IQOTHNCCD lung cancer dataset. A state-of-the-art comparison has been done for the given dataset for classification accuracy. The proposed approach outperformed others and achieves a classification accuracy of 98.33%.

Lung Cancer, Convolutional Neural Network (CNN), Deep Learning, Machine Learning,Computer-aided diagnosis, Medical Image