Efficient MRI Segmentation and Detection of Brain Tumor using Convolutional Neural Network
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2019, Vol 10, Issue 4
Abstract
Brain tumor is one of the most life-threatening diseases at its advance stages. Hence, detection at early stages is very crucial in treatment for improvement of the life expectancy of the patients. magnetic resonance imaging (MRI) is being used extensively nowadays for detection of brain tumors that requires segmenting huge volumes of 3D MRI images which is very challenging if done manually. Thus, automatic segmentation of the images will significantly lessen the burden and also improve the process of diagnosing the tumors. This paper presents an efficient method based on convolutional neural networks (CNN) for the automatic segmentation and detection of a brain tumor using MRI images. Water cycle algorithm is applied to CNN to obtain an optimal solution. The developed technique has an accuracy of 98.5%.
Authors and Affiliations
Alpana Jijja, Dr. Dinesh Rai
Keywords
Related Articles
- EP ID EP552370
- DOI 10.14569/IJACSA.2019.0100466
- Views 96
- Downloads 0
Service Design for Developing Multimodal Human-Computer Interaction for Smart Tvs
A Smart TV integrates Internet and Web features into a TV, as well convergence between computer and TV and can utilize as a computer. Smart TV devices facilitate the curation of content by combining Internet-based inform...
Dynamic Bandwidth Allocation in LAN using Dynamic Excess Rate Sensing
Today human and information processing system both need rapid access to anything they want on the internet. To fulfill these needs more and more internet service providers with a large amount of bandwidth are introducing...
A Comparison Review based on Classifiers and Regression Models for the Investigation of Flash Floods
Several regions of the world have been affected by one of the natural disasters named as flash floods. Many villagers who live near stream or dam, they suffer a lot in terms of property, cattle and human lives loss. Conv...
An efficient user scheduling scheme for downlink Multiuser MIMO-OFDM systems with Block Diagonalization
The combination of multiuser multiple-input multiple-output (MU-MIMO) technology with orthogonal frequency division multiplexing (OFDM) is an attractive solution for next generation of wireless local area networks (WLANs...
Modeling the Cut-off Frequency of Acoustic Signal with an Adaptative Neuro-Fuzzy Inference System (ANFIS)
An Adaptative Neuro-Fuzzy Inference System (ANFIS), new flexible tool, is applied to predict the cut-off frequencies of the symmetric and the anti-symmetric circumferential waves (Si and Ai, i=1,2) propagating around an...