Lung Cancer Detection using CT Scan Images
Syed Abudhagir Umar1, Chenigaram Abhigna2, Cheemalapati Venkata Vignesh3, Teki Rohith Raj4
1Dr. Syed Abudhagir Umar, Department of Electronics and Communication Engineering, B V Raju Institute of Technology, Vishnupur (Telangana), India.
2 Chenigaram Abhigna, Department of Electronics and Communication Engineering, B V Raju Institute of Technology, Vishnupur (Telangana), India.
3Cheemalapati Venkata Vignesh, Department of Electronics and Communication Engineering, B V Raju Institute of Technology, Vishnupur (Telangana), India.
4Teki Rohith Raj, Department of Electronics and Communication Engineering, B V Raju Institute of Technology, Vishnupur (Telangana), India.
Manuscript received on 02 August 2022 | Revised Manuscript received on 07 August 2022 | Manuscript Accepted on 15 October 2022 | Manuscript published on 30 October 2022 | PP: 1-5 | Volume-12 Issue-1, October 2022. | Retrieval Number: 100.1/ijeat.A37751012122 | DOI: 10.35940/ijeat.A3775.1012122
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© 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: Lung cancer is a fatal disease that takes numerous lives every year around the world. However, detecting this disease in its initial stages can help save the lives of the people. CT imaging is the best technique used for imaging in the field of medical sciences. It is used by doctors but it is hard for medical examiners to decipher and recognize cancer through the computer-assisted tomography scan images. Hence, Computer-aided diagnosis will be very supportive for the medical examiners to identify and recognize the cancerous nodules in cells precisely. The primary agenda of the project is to assess diverse computer based methods, explore present finest method, deduce its limitations and setbacks. Then, proposing a latest model with upgrades and advancements to the present leading model. Techniques applied for diagnosis of lung can cerare organized based on the precision. Numerous methods were surveyed on every stride and the complete limitations and setbacks were identified. A lot of techniques had low precision and few had high precision. But none of those were satisfying. Therefore, our target is to increase the precision of the model.
Keywords: Computer-Aided Diagnostic, CT Scan Images, Cancer, Image Processing, Lung Cancer Diagnosis.
Scope of the Article: Image Processing and Pattern Recognition