Optimal Diagnosis of Lung Cancer using CT Images
Karthikeyan S1, Navin Kumar M2, Aishwarya M R3, Deva Subramanian S4, Guru Lakshana M5
1Dr. Karthikeyan S, Associate Professor, Department of ECE, Malla Reddy Engineering College and Management Sciences, Kistapur Village, Medchal Mandal, Ranga Reddy, (Telangana), India.
2Mr. Navinkumar M, Assistant Professor, Department of ECE, Sri Krishna College of Technology, Coimbatore (Tamil Nadu), India.
3Ms. Aishwarya M R, Student, Department of ECE, Sri Krishna College of Technology, Coimbatore (Tamil Nadu), India.
4Mr. Deva Subramanian S, Student, Department of ECE, Sri Krishna College of Technology, Coimbatore (Tamil Nadu), India.
5Ms. Guru Lakshana M, Student, Department of ECE, Sri Krishna College of Technology, Coimbatore (Tamil Nadu), India.
Manuscript received on 16 October 2019 | Revised Manuscript received on 25 October 2019 | Manuscript Published on 02 November 2019 | PP: 2695-2699 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B13300982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1330.0982S1119
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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: According to the American Cancer Society, lung cancer is the second most widespread cancer and the leading cause of cancer deaths in both men and women. The death rate of lung cancer every year is greater than that of colon, breast, and prostate cancers combined. CT scan is a non-invasive method for diagnosis of any ailment, and can be used to detect lung cancer as well. The proposed project involves cell detection using image processing techniques. Because the time is a very important factor in cancer treatment, especially in cancers such as the lung, imaging techniques are used to accelerate diagnosis. The image processing paired with data analysis techniques helps us diagnose the particular type of cancer by comparing the output of the CT scan to an available database of images. This improves accuracy and reduces the time required for the diagnosis. Features of the image under test are extracted and analysed, and the decision regarding the morphological characteristics of the image are made. This helps us arrive at a decision regarding the nature of the image.
Keywords: CT Scan, Image Processing, Segmentation, Feature Extraction.
Scope of the Article: Image Processing and Pattern Recognition