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Fangary, Laila El
- Algorithms of Deep Learning:Convolutional Neural Network Role with Colon Cancer Disease
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Authors
Affiliations
1 Information Systems Department ,Faculty of Computers and Artificial Intelligence, Helwan University, EG
2 Information Systems Department, Faculty of Computers and Artificial Intelligence, Helwan University, EG
1 Information Systems Department ,Faculty of Computers and Artificial Intelligence, Helwan University, EG
2 Information Systems Department, Faculty of Computers and Artificial Intelligence, Helwan University, EG
Source
International Journal of Advanced Networking and Applications, Vol 13, No 1 (2021), Pagination: 4827-4832Abstract
The world's third most serious and lethal cancer rankings are colon cancer. Like cancer, the most important stage of early diagnosis is. Deep learning has become a leading learning tool for object detection and its successes in advancing the analysis of medical images have attracted attention. Convolutionary neural networks (CNNs), which play an indispensable role in the detection and potential early diagnose of colon cancer, are the most popular method of deep learning algorithms for this purpose. In this article we hope to take a look at the progress of colonic cancer analysis by studying profound learning practices. This study provides an overview of popular profound study algorithms used in analysis of colon cancer. All studies in the fields of colon cancer, including detection, classification as well as segmentation and survival prediction, will then be collected. Finally, we will conclude the work by summarizing the latest deep learning practices in analysis of colon cancer, a critical examination of the challenges and proposals for future research.Keywords
Deep Learning, Colon Cancer, Medical Image Analysis, Convolutional Neural Networks.Full Text
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