Subject
Colon CancerHistopathological Images
Adenocarcinoma
Deep Learning
VGG
Machine Learning
Convolutional Neural Network
Artificial Neural Network
Random Forest
Support Vector Machines
KNN
ResNet
MobileNet
Date
2023-01-20
Metadata
Show full item recordAbstract
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.Department
Computer SciencePublisher
Academic PressBook title
Applications of Artificial Intelligence in Medical Imaging.ae974a485f413a2113503eed53cd6c53
https://doi.org/10.1016/B978-0-443-18450-5.00001-3