ew 18(20): e17

Research Article

A Review On Automatic Detection of Brain Tumor Using Computer Aided Diagnosis System Through MRI

Download1067 downloads
Cite
BibTeX Plain Text
  • @ARTICLE{10.4108/eai.12-9-2018.155747,
    author={Meera R and Dr. Anandhan, P},
    title={A Review On Automatic Detection of Brain Tumor Using Computer Aided Diagnosis System Through MRI},
    journal={EAI Endorsed Transactions on Energy Web and Information Technologies},
    volume={5},
    number={20},
    publisher={EAI},
    journal_a={EW},
    year={2018},
    month={9},
    keywords={MRI, Segmentation, CAD, Computer Tomography, Preprocessing, Enhancement},
    doi={10.4108/eai.12-9-2018.155747}
}
  • Meera R
    Dr. Anandhan, P
    Year: 2018
    A Review On Automatic Detection of Brain Tumor Using Computer Aided Diagnosis System Through MRI
    EW
    EAI
    DOI: 10.4108/eai.12-9-2018.155747
Meera R1,*, Dr. Anandhan, P2
  • 1: Fulltime Research Scholar, Anna University, Chennai
  • 2: Professor, Department of ECE,Vel Tech Multi Tech Dr.Rangarajan Dr.Sakunthala Engineering College, Chennai
*Contact email: rathameera4041993@gmail.com

Abstract

In diagnosing brain tumor using Magnetic Resonance Imaging (MRI) plays a major role in complicated stages. To extract the images, it uses a kind of nuclear magnetic resonance technique. To identify the exact region where the tumor is present is the most important task in the segmentation process. The most challenging and complicated medical image processing technique Brain image segmentation. The researchers are working towards to develop effective procedure for segmenting MRI images. In this research article Pre-processing, Enhancement and Segmentation process are deeply surveyed.

Keywords
MRI, Segmentation, CAD, Computer Tomography, Preprocessing, Enhancement
Received
2018-07-06
Accepted
2018-08-25
Published
2018-09-12
Publisher
EAI
http://dx.doi.org/10.4108/eai.12-9-2018.155747

Copyright © 2018 Meera.R et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.