Open AccessBrain tumor detection from MRI images using deep learning techniques
Author(s) -
P. Gokila Brindha,
M Kavinraj,
P Manivasakam,
P. S. Prasanth
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1055/1/012115
Subject(s) - brain tumor , computer science , artificial intelligence , convolutional neural network , magnetic resonance imaging , deep learning , brain cancer , artificial neural network , convolution (computer science) , pattern recognition (psychology) , cancer , radiology , medicine , pathology
Brain tumor is the growth of abnormal cells in brain some of which may leads to cancer. The usual method to detect brain tumor is Magnetic Resonance Imaging(MRI) scans. From the MRI images information about the abnormal tissue growth in the brain is identified. In various research papers, the detection of brain tumor is done by applying Machine Learning and Deep Learning algorithms. When these algorithms are applied on the MRI images the prediction of brain tumor is done very fast and a higher accuracy helps in providing the treatment to the patients. These prediction also helps the radiologist in making quick decisions. In the proposed work, a self defined Artificial Neural Network (ANN) and Convolution Neural Network (CNN) is applied in detecting the presence of brain tumor and their performance is analyzed.