Lung Cancer Detection and Classification Using Deep CNN
S. Sasikala1, M. Bharathi2, B. R. Sowmiya3
1S. Sasikala, Associate Professor, Department of Electronics and Communication Engineering, Kumaraguru College of Technology, Coimbatore (TamilNadu), India.
2M. Bharathi, Professor, Department of Electronics and Communication Engineering, Kumaraguru College of Technology, Coimbatore (TamilNadu), India.
3B.R. Sowmiya, PG Scholar, Professor, Department of Electronics and Communication Engineering, Kumaraguru College of Technology, Coimbatore (TamilNadu), India.
Manuscript received on 10 December 2018 | Revised Manuscript received on 17 December 2018 | Manuscript Published on 30 December 2018 | PP: 259-262 | Volume-8 Issue- 2S December 2018 | Retrieval Number: BS2713128218/19©BEIESP
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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: Lung cancer is one of the most killerdiseases in the developing countries and the detection of the cancer at the early stage is a challenge. Analysis and cure of lung malignancy have been one of the greatest difficulties faced by humans over the most recent couple of decades. Early identification of tumor would facilitate in sparing a huge number of lives over the globe consistently. This paper presents an approach which utilizes a Convolutional Neural Network (CNN) to classify the tumors found in lung as malignant or benign. The accuracy obtained by means of CNN is 96%, which is more efficient when compared to accuracy obtained by the traditional neural network systems.
Keywords: Lung cancer, Computed Tomography, Chest CT image, Neural Network, Deep Learning, Convolutional Neural Network.
Scope of the Article: Communication