This paper is published in Volume-4, Issue-6, 2018
Area
Machine Learning
Author
Sakshi Sharma
Org/Univ
Chandigarh University, Ajitgarh, Punjab, India
Pub. Date
27 November, 2018
Paper ID
V4I6-1246
Publisher
Keywords
Detection on lung cancer, CT scan images, SVM, Naive Bayes

Citationsacebook

IEEE
Sakshi Sharma. Detection of lung cancer using computerized tomography scan: A review, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Sakshi Sharma (2018). Detection of lung cancer using computerized tomography scan: A review. International Journal of Advance Research, Ideas and Innovations in Technology, 4(6) www.IJARIIT.com.

MLA
Sakshi Sharma. "Detection of lung cancer using computerized tomography scan: A review." International Journal of Advance Research, Ideas and Innovations in Technology 4.6 (2018). www.IJARIIT.com.

Abstract

Lung cancer is very effective and causes deadly diseases among human. It is detected in the last stage, not in the initial stage, which can give the worst results. It also defects other parts of the body. Lung cancer has two types i.e non-small lung cancer and small lung cancer. Smoking can be one of the main reason of lung cancer. This can be diagnosis by the different techniques Many techniques were used to detect lung cancer, but CT is better for accurate results using imaging techniques. CT scan is helpful in predicting the performance of classification. Classification plays a major role in image analysis. Firstly, ct scan image as an input pass to the system through the image processing and then segmentation is performed. The main components of the structure is ct scan images, segmentation, nodule detection, feature extraction. Training data and testing data is used to determine the accuracy of both the algorithms and check the better accuracy. The main objective is to evaluate the computed tomography technique through SVM and then compare it with Naive Bayes to increase the accuracy, but there are some limitations to reach 100%.
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