Lung cancer prediction and Stage classification in CT Scans Using Convolution Neural Networks -A Deep learning Model

Medical image processing has recently become popular in the last two decades. CT scans provide detailed images of interior organs, bones, soft tissue, and blood arteries. Different segmentation approaches and feature extraction techniques is used for nodule extraction from the ct images. Deep learning techniques is used for lung cancer detection and stage classification to produce better results. This paper discusses different deep learning techniques. Lung cancer dataset was used on the different pre-trained models such as AlexNet, ResNet18, Googlenet, and ResNet50.The performance of the models are calculated using metrics such as confusion matrix, precision, recall, specificity, and f1-score. In this paper the models are modified with different number of layers and optimization techniques to generate a new image classification.