Open AccessBrain Tumor Segmentation in MRI Images using Convolution Neural Networks
Author(s) -
Esther Rani P,
Medavarapu T N D Sri Harsha,
Anil Kumar Singh,
Sujeet Kumar Singh
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b3817.118419
Subject(s) - computer science , artificial intelligence , segmentation , brain tumor , task (project management) , magnetic resonance imaging , convolution (computer science) , convolutional neural network , identification (biology) , artificial neural network , pattern recognition (psychology) , computer vision , matlab , image segmentation , deep learning , radiology , medicine , pathology , botany , management , biology , economics , operating system
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.