Lung Cancer Detection using Nearest Neighbour Classifier
R. Madana Mohana1, R. Delshi Howsalya Devi2, Anita Bai3
1Dr. R. Madana Mohana, Professor, Department of Computer Science & Engineering, Bharat Institute of Engineering and Technology, Hyderabad (Telangana), India.
2Dr. R. Delshi Howsalya Devi, Associate Professor, Department of Computer Science & Engineering, Bharat Institute of Engineering and Technology, Hyderabad (Telangana), India.
3Dr. Anita Bai, Associate Professor, Department of Computer Science & Engineering, Bharat Institute of Engineering and Technology, Hyderabad (Telangana), India.
Manuscript received on 19 October 2019 | Revised Manuscript received on 25 October 2019 | Manuscript Published on 02 November 2019 | PP: 3641-3645 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B14580982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1458.0982S1119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: One of the most precarious diseases is lung cancer. Lung cancer detection is one of the main challenging dilemma nowadays. Most of the cancer cells are overlies with each other. It is tough to detect the cell but also important to identify the existence of cancer cells in the early stage unless unable to prevent. According to 2018 reports, 17 million new lung cancer cases are identified worldwide. The Computer Tomography can be used for diagnosis of cancer with image processing. In this research, we proposed two steps of process for diagnosing the presence of cancer either benign or malignant. In the first step, features are extracted by using GLCM. In the second step, the lung cancer cells are classified either benign or malignant by using Nearest Neighbour classifier. Experimental results demonstrated that the proposed approach performance is 98.76% classification accuracy for diagnosing the lung cancer data.
Keywords: Lung Cancer, Computer Tomography, GLCM Features, NN- Classifier.
Scope of the Article: Advanced Computer Networking