Deep Learning based Brain Tumor Detection
Anjanadevi B1, Hima Bindu V2, Nitish S3, Yunesha M4
1Anjanadevi Bondalapati*, IT Dept, MVGR College of Engg, Vizianagaram, AP, India.
2Hima Bindu V, IT Dept, MVGR, Vzm, A.P.
3Nitish S,IT Dept, MVGR, Vzm, AP.
4Yunesha M, IT Dept, MVGR, Vzm, AP,
Manuscript received on April 20, 2020. | Revised Manuscript received on April 30, 2020. | Manuscript published on May 10, 2020. | PP: 874-877 | Volume-9 Issue-7, May 2020. | Retrieval Number: G5454059720/2020©BEIESP | DOI: 10.35940/ijitee.G5454.059720
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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: In current technology era, to sustain and provide healthy life to humans it is necessary to detect the diseases in early stages. We are focused on Brain tumour detection process, it is very challenging task in medical image processing. Through early diagnosis of brain, we can improve treatment possibilities and increase the survival rate of the patients. Recently, deep learning plays a major role in computer vision, using deep learning techniques to reduction of human judgements in the process of diagnosis. Proposed model is efficient than traditional model and provides best accuracy values. The experimental results are clearly showing that, the proposed model outperforms in the detection of brain tumour images.
Keywords: Deep Learning, Data Augmentation, Normalization, Transfer Learning.
Scope of the Article: Deep Learning