Detection of Pancreatic Tumor using Bacterial Foraging Algorithm
K. Sujatha1, Ponmagal.R. S2, Yasoda. K3, M. Anand4, V. Karthikeyan5, V. Srividhya6, N.P.G. Bhavani7, Su-Qun Cao8
1K.Sujatha, Professor, Department of Electronic Information Engineering, Dr. MGR Educational & Research Institute, SRM Institute of Science and Technology, India.
2Ponmagal.R. S, Professor, Department of Electronic Information Engineering, Dr. MGR Educational & Research Institute, SRM Institute of Science and Technology, India.
3Yasoda. K, Professor, Department of Electronic Information Engineering, Dr. MGR Educational & Research Institute, SRM Institute of Science and Technology, India.
4M. Anand, Professor, Department of Electronic Information Engineering, Dr. MGR Educational & Research Institute, SRM Institute of Science and Technology, India.
5V. Karthikeyan, Professor, Department of Electronic Information Engineering, Dr. MGR Educational & Research Institute, SRM Institute of Science and Technology, India.
6V. Srividhya, Professor, Department of Electronic Information Engineering, Dr. MGR Educational & Research Institute, SRM Institute of Science and Technology, India.
7N.P.G. Bhavani, Professor, Department of Electronic Information Engineering, Dr. MGR Educational & Research Institute, SRM Institute of Science and Technology, India.
8Su-Qun Cao, Professor, Department of Electronic Information Engineering, Dr. MGR Educational & Research Institute, SRM Institute of Science and Technology, India.
Manuscript received on 06 June 2019 | Revised Manuscript received on 30 June 2019 | Manuscript Published on 04 July 2019 | PP: 844-848 | Volume-8 Issue-1S4 June 2019 | Retrieval Number: A11550681S419/2019©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: Study and forecast are the central objectives taken into consideration for diagnosis of pancreatic tumor. The detection of pancreatic tumor in patients in premature stage increases the chance of survivability for the patients rather than diagnosis either in malignant stage. If the tumor is detected in the chronic stage, the possibility of survival for the patient is very less. Furthermore, the tumor forecasted in the premature stage will increase the survival rate of the patient based on appropriate medication and treatment. Currently, the forecast of pancreatic tumor in the premature stage focuses on attributed based image analysis of Magnetic Resonance Imaging (MRI). The MRI pancreatic images obtained from MRI scan forms the source of images to detect the pancreatic tumors at premature stage. A distinct detection method for identification of pancreatic tumors using image texture characters is proposed in this work. The
Keywords: Algorithm Pancreatic Tumor Image Method.
Scope of the Article: Algorithm Engineering