Brain Tumor Detection and Classification using Convolution Neural Network
Manjunath S1, Sanjay Pande M B2, Raveesh B N3, Madhusudhan G K4

1Manjunath S, Research Scholar, Department of Computer Science and Engineering, Jain University, Bengaluru (Karnataka), India.
2Dr. Sanjay Pande M B, Professor and Head, Department of Computer Science and Engineering, GMIT, Davangere (Karnataka), India.
3Madhusudhan G K, Assistant Professor, Department of Computer Science and Engineering, VVIET, Mysuru (Karnataka), India.
4Dr. Raveesh B N, Head and Professor, Department of Psychiatry Mysore Medical College, Mysuru (Karnataka), India.
Manuscript received on 21 May 2019 | Revised Manuscript received on 11 June 2019 | Manuscript Published on 27 June 2019 | PP: 34-40 | Volume-8 Issue-1C May 2019 | Retrieval Number: A10080581C19/2019©BEIESP
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Abstract: Understanding Human activity has lead researchers to work on one of the major organ of human body namely Brain. The smooth function of Human Brain enhances the activities of human body. The systematic working of Human brain is affected by various causes. In the present work, we have taken one such cause that is Brain tumor, which is mainly due to abnormal growth of Cells in Brain. The recognition of Brain is generally done by Magnetic resonance imaging (MRI). The major drawback of this is to find the exact location/position. Hence it becomes important to find the means and methods to detect, identify and classify the disease based upon the image. The proposed work involves Extraction to grading of Tumor to be relevant class. The complexity of the present work is due to conversion of the extracted image as symbolic data and use of Convolution Neural networks. The experimentation were corroborated with BPNN and CNN classifier.
Keywords: Convolution, Neural Network, Brain Tumor, LBP, Fuzzy-C.
Scope of the Article: Classification