Brain Tumor Grade Detection by Using ANN
S. Josephine1, S. Murugan2
1S.Josephine, Research Scholar, Department of Computer Science, Nehru Memorial College, Tiruchirappalli, Tamilnadu, India.
2S.Murugan, Associate Professor and Research Advisor, department, Department of Computer Science, Nehru Memorial College, Tiruchirappalli, Tamilnadu, India.
Manuscript received on July 30, 2019. | Revised Manuscript received on August 25, 2019. | Manuscript published on August 30, 2019. | PP: 4175-4178 | Volume-8 Issue-6, August 2019. | Retrieval Number: F8582088619/2019©BEIESP | DOI: 10.35940/ijeat.F8582.088619
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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: Brain tumor is death threatening disease, the early detection helps to extend the life time. Practically, the micro analysis of tissues only confirms the disease severity. Hence, a computer aided method is proposed to categorize brain tumors as benign and malignant by using Feed forward network. The existing works assign features as much of pixel counts. However, the proposed method eliminates the feature size by using significant features according to the tumor and brain anatomy. The network attains 96% of accuracy and compared against existing works.
Keywords: ANN, GLCM, Gober Filter, Morphology operator, MRI.