Author:
Chaturvedi Pragya,Jhamb Anuj,Vanani Meet,Nemade Varsha
Abstract
Abstract
In all the disease that have existed in mankind lung cancer has emerged as one of the most fata one time and again. Also, it is one of the most common and contributing to deaths among all the cancers. Cases of lung cancer are increasing rapidly. There are about 70,000 cases per year in India. The disease has a tendency to be asymptomatic mostly in its earlier stages thus making it nearly impossible to detect. That’s why early cancer detection plays an important part in saving lives. An early detection can give a patient a better chance to cure and recover. Technology plays a major role in detecting cancer efficiently. Many researchers have proposed different methods based on their studies. In recent times, to use computer technology to solve this problem, several computer-aided diagnosis (CAD) techniques as well as system have been proposed, developed as well as emerged. Those systems use various Machine learning techniques as well as deep learning techniques, there also have been several methods based off of image processing-based techniques to predict the malignancy level of cancer. Here, in this paper, the aim will be focussed onto list, discuss, compare and analyse several methods in image segmentation, feature extraction as well as various techniques to classify and detect lung cancer in there early stages.
Cited by
54 articles.
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