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Reseach Article

Brain Tumor Detection through MR Images: A Review of Segmentation Techniques

by Madhvi Arya, Reecha Sharma
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 153 - Number 7
Year of Publication: 2016
Authors: Madhvi Arya, Reecha Sharma

Madhvi Arya, Reecha Sharma . Brain Tumor Detection through MR Images: A Review of Segmentation Techniques. International Journal of Computer Applications. 153, 7 ( Nov 2016), 33-37. DOI=10.5120/ijca2016912109

@article{ 10.5120/ijca2016912109,
author = { Madhvi Arya, Reecha Sharma },
title = { Brain Tumor Detection through MR Images: A Review of Segmentation Techniques },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2016 },
volume = { 153 },
number = { 7 },
month = { Nov },
year = { 2016 },
issn = { 0975-8887 },
pages = { 33-37 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2016912109 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T23:58:32.090913+05:30
%A Madhvi Arya
%A Reecha Sharma
%T Brain Tumor Detection through MR Images: A Review of Segmentation Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 153
%N 7
%P 33-37
%D 2016
%I Foundation of Computer Science (FCS), NY, USA

In this paper, a review on computer-based methods which defines the tumor region in the brain using MRI images is discussed. Various image processing techniques are reviewed in this paper which helps to enhance the images for the computerized detection of brain tumor. Magnetic Resonance Imaging (MRI) is mostly used to obtain medical imaging with very high quality. MRI is a very advanced technique which provides very rich information about size, shape and location of brain tumors without any need to expose the patient to a high ionization radiation. In medical imaging, segmentation is used to segment abnormal tissues from normal tissues and reliable, accurate, and automatic segmentation of these structures and tissues can results in improved diagnosis and treatment of disease. Digital Image Processing provides number of methods to study bio-medical images from different aspects. The paper focuses on to provide overview for different segmentation techniques involved in brain tumor detection.

  1. Roland Winkler, Frank Klawonn, Rudolf Kruse,” Problems of Fuzzy c-Means Clustering and Similar Algorithms with High Dimensional Data Sets”, 2012.
  2. Ekta Sharma, Nidhi Seth, “A Survey on the MRF Model Using Image Segmentation Techniques”, In IJARIIE, Vol-2 Issue-3, 2016.
  3. Julie DELON, Agnes DESOLNEUX, Jose-Luis LISANI, Ana-Belen PETRO, “A non-parametric approach for histogram segmentation”, 2011
  4. W. M. Wells, W.E.L Grimson, R. Kikinis, F.A. Jolesz, “Adaptive Segmentation of MRI Data”, In IEEE transactions on Medical Imaging, volume 15, No. 4, august 1996.
  5. Jin Liu, Min Li, Jianxin Wang, Fangxiang Wu, Tianming Liu, and Yi Pan, “A Survey of MRI-Based Brain Tumor Segmentation Methods”, ISSN 1007-0214 04/10 pp578-595 Volume 19, Number 6, December 2014.
  6. R.Yogamangalam, B.Karthikeyan, “Segmentation Techniques Comparison in Image Processing”, IJET, ISSN:0975-4024 Vol 5 No 1 Feb-Mar 2013.
  7. Eltaher Mohamed Hussein, Dalia Mahmoud Adam Mahmoud’ “Brain Tumor Detection Using Artificial Neural Networks, Journal of Science and Technology Vol. 13, No. 2, December 2012.
  8. Kusum Rani, Reecha Sharma,” Study of Different Image fusion Algorithm”, International Journal of Emerging Technology and Advanced Engineering”, (ISSN 2250-2459, Volume 3, Issue 5, May 2013).
  9. Y. Zhang, L. Wu “An MR Brain Images Classifier via Principal Component Analysis and Kernel Support Vector Machine”, Progress in Electromagnetics Research, Vol. 130, 369-388, august 2012.
  10. Bing Nan Li, Chee Kong Chui, Stephen Chang, S.H. Ong, “Integrating Spatial Fuzzy Clustering with level set methods for automates medical image segmentation”, Computers in Medical and Imaging 41(2011) 1-10.
  11. Arashdeep Kaur, “An Automatic Brain Tumor Extraction System using Different Segmentation Methods”, 2016 Second International Conference on Computational Intelligence & Communication Technology.
  12. K. S. Angel Viji, Dr J. Jayakumari, “Modified Texture Based Region Growing Segmentation of MR Brain Images”, 2013 IEEE Conference on Information and Communication Technologies (ICT 2013).
  13. Harneet Kaur, Sukhwinder Kaur,“Improved Brain Tumor Detection Using Object Based Segmentation”, (IJETT) – Volume 13 Number 1 – Jul 2014.
  14. Ehab F. Badran, Esraa Galal Mahmoud, and Nadder Hamdy, “An Algorithm for Detecting Brain Tumors in MRI Images”, 2010.
  15. B. Sathees, Dr. R. Anbu Selvi, “Feature Extraction Using Image Mining Techniques to Identify Brain Tumors”, IEEE International Conference on ICIIECS'15.
  16. Sudipta Roy, Sanjay Nag , Indra Kanta Maitra, Samir Kumar Bandyopadhyay, ”A Review on Automated Brain Tumor Detection and Segmentation from MRI of Brain”.
  17. Kusum Rani, Reecha Sharma, “Fusion of CT and MRI images using Discrete Multiwavelet Transform”, International Journal of Computer Trends and Technology (IJCTT) - ISSN: 2231-2803, volume4 Issue5–May 2013.
  18. Eman Abdel-Maksoud, Mohammed Elmogy, Rashid Al-Awadi, “Brain tumor segmentation based on a hybrid clustering technique”, Egyptian Informatics Journal (2015) 16,71–81, February 2015.
  19. Ilya Pollak, Alan S. Willsky, Hamid Krim, “Image Segmentation and Edge Enhancement with Stabilized Inverse Diffusion Equations”. IEEE transactions on image processing, vol. 9, no. 2, February 2000.
  20. Lamia Jaafar Belaid, Walid Mourou, “Image segmentation: a Watershed transformation Algorithm”, March 2009.
  21. M. Madheswaran and D. Anto Sahaya Dhas, “Classification of brain MRI images using support vector machine with various Kernels”, ISSN 0970-938X- April 2015.
  22. Girja Sahu, P. Bhaiya, “A Survey Paper Based on the Classification of MRI Brain Images Using Soft Computing Techniques”, IJETAE, ISSN 2250-2459, Volume 4, Issue 12, December 2014.
  23. Sun Hyung Kim, Vladimir Fonov, Joe Piven, John Gilmore, Clement Vachet, Guido Gerig, D. Louis Collins, Martin Styner,”Spatial Intensity Prior Correction for Tissue Segmentation in the Developing Human Brain”, Proc IEEE Symp Biomed Imaging, 2011 :: 2049-2052 doi:10.1109 ISBI.2011.5872815.
  24. Mohammed Sabbih Hamoud Al-Tamimi, Ghazali Sulong, “Tumor Brain Detection Through Mr Images: A Review Of Literature”, ISSN: 1992-8645, Vol. 62 No.2,2014.
Index Terms

Computer Science
Information Sciences


Magnetic resonance imaging (MRI) Image segmentation Digital Image Processing (DIP)