Brain Tumor Segmentation in MRI Images using Convolution Neural Networks
Esther Rani P1, Mahadev Venkata Sai Harsha2, Anil Singh3, Sujeet Singh4
1Esther Rani P*, Professor, Electronics and Communication Engineering, Vel Tech Rangarajan Dr. Sagunthala R &D Institute of Science and Technology, Avadi, Chennai, India.
2Mahadev Venkata Sai Harsha, Electronics and Communication Engineering, Vel Tech Rangarajan Dr. Sagunthala R &D Institute of Science and Technology, Avadi, Chennai, India.
3Anil Singh, Electronics and Communication Engineering, Vel Tech Rangarajan Dr. Sagunthala R &D Institute of Science and Technology, Avadi, Chennai, India.
4Sujeet Singh, Electronics and Communication Engineering, Vel Tech Rangarajan Dr. Sagunthala R &D Institute of Science and Technology, Avadi, Chennai, India.
Manuscript received on November 15, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on November 30, 2019. | PP: 2051-2054 | Volume-8 Issue-4, November 2019. | Retrieval Number: B3817078219/2019©BEIESP | DOI: 10.35940/ijrte.B3817.118419
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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: Medical image processing is an important task in current scenario as more and more humans are diagnosed with various medical issues. Brain tumor (BT) is one of the problems that is increasing at a rapid rate and its early detection is important in increasing the survival rate of humans. Detection of tumor from Magnetic Resonance Image (MRI) of brain is very difficult when done manually and also time consuming. Further the tumors assume different shapes and may be present in any portion of the brain. Hence identification of the tumor poses an important task in the lives of human and it is necessary to identify its exact position in the brain and the affected regions. The proposed algorithm makes use of deep learning concepts for automatic segmentation of the tumor from the MRI brain images. The algorithm is implemented using MATLAB and an accuracy of 99.1% is achieved.
Keywords: Brain Tumor, Segmentation, Data Augmentation, Convolution Neural Networks, Deep Learning.
Scope of the Article: Deep Learning.