Spotting Brain and Pancreatic Tumor Identification Through SRM Segmentation and Naive Bayes Method
Jithendra Reddy. D1, Arun Prasath. T2, Pallikonda Rajasekaran. M3, Vishnuvarthanan. G4

1D. Jithendra Reddy, Department of Instrumentation and Control Engineering, Kalasalingam Academy of Research and Education College, Krishnankoil (Tamil Nadu), India.
2T. Arun Prasath, Department of Biomedical Engineering, Kalasalingam Academy of Research and Education College, Krishnankoil (Tamil Nadu), India.
3M. Pallikonda Rajasekaran, Department of Electronics and Communication Engineering, Kalasalingam Academy of Research and Education College, Krishnankoil (Tamil Nadu), India.
4G. Vishnuvarthanan, Department of Biomedical Engineering, Kalasalingam Academy of Research and Education College, Krishnankoil (Tamil Nadu), India.
Manuscript received on 29 November 2019 | Revised Manuscript received on 18 December 2019 | Manuscript Published on 31 December 2019 | PP: 339-343 | Volume-8 Issue-4S2 December 2019 | Retrieval Number: D10761284S219/2019©BEIESP | DOI: 10.35940/ijrte.D1076.1284S219
Open Access | Editorial and Publishing 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: Imaging techniques empower researchers and medical practitioners to evaluate disorders and activities inside the human brain and pancreases earlier than performing invasive surgery. Amid sundry medical image modalities, magnetic resonance imaging dispenses utmost preferred contrast information about brain tissues from a diversity of excitation sequences. Therefore, remedy forethought is a key to the midway to recover grace lifespan of oncological patients. Here proposed work through brain image and pancreases image with respective MR image and CT scan image through filters DBCWMF and histogram equation, Segmentation with SRM and extracted Feature GLCM and Naive Bayes approach with hospital database and TCIA database.
Keywords: Filters DBCWMF, Pancreases, Brain, GLCM, SRM, Naive Bayes.
Scope of the Article: Biomedical Computing