Automated detection of colon cancer using deep learning

Abstract

Colon cancer is a type of cancer that affects the large population. In the beginning, small ploys are formed in the large intestine, which if left untreated become cancer. Detection of colon cancer in its early stages reduces the risk of life to large extent and makes treatment easier and reduces the cost of treatment. The traditional way of detection of colon cancer is very time-consuming and often can be wrong if not done by a skilled person. The development of deep learning has enabled us to detect colon cancer accurately using histopathological images. In this chapter different pretrained models and techniques are used. The accuracy of results is very good; using ResNet50 99.8% accuracy is achieved on the test data which is very good. Using these techniques, the time for detection of colon cancer can be reduced significantly.