AN EFFICIENT APPROACH FOR MR BRAIN IMAGE MULTILEVEL SEGMENTATION AND PERFORMANCE ANALYSIS

Authors

  • S. Sri Devi PG scholar, Communication systems, Rajas International Institute of Technology for Women, Nagercoil, Tamil Nadu, India
  • Abhisha Mano Assistant professor, Department of ECE, Rajas International Institute of Technology for Women, Nagercoil, Tamil Nadu, India

DOI:

https://doi.org/10.29121/ijetmr.v5.i3.2018.195

Keywords:

Magnetic Resonance Imaging (MRI), segmentation, Spatial Fuzzy C-Means (SFCM), Firefly Optimization (FO), Gray matter (GM), White Matter (WM), Cerebrospinal fluid (CSF)

Abstract

Complex organs can be analysed by using the Magnetic Resonance Image (MRI). This kind of imaging helps the doctors for diagnosis and treatment of neurological diseases. Brain is the complex organ of the human body. It controls the all the organs in our body. Accurate segmentation and analysis of brain tissues such as Gray Matter and White Matter help the doctors for the diagnosing of some complex diseases and neuro surgery. In this paper an efficient method for the segmentation of Gray Matter, White Matter and Cerebrospinal Fluid, Skull regions from MRI brain image using Spatial Fuzzy C-Means was proposed. However, accuracy of this algorithm is not efficient for abnormal brain. To improve the accuracy of segmentation Firefly Optimization algorithm was implemented. Proposed method was implemented using MATLAB 8.6.0.267246 (R2015a) and various parameters were analysed.

Downloads

Download data is not yet available.

References

Sudipta Roy, Atanu Saha and Samir K. Bandyopadhyay, “Brain Tumor Segmentation and Quantification from MRI of Brain”,Journal of Global Research in Computer Science, Vol.2 No. 4, April 2011.

Pratik Vinayak Oak and R. S. Kamathe, “Contrast Enhancement of Brain MRI Images using Histogram Based Techniques ”,International Journal of Innovative Research in Electrical, Electronics, Instrumentation, and Control Engineering, Vol.1, Issue 3, June 2013.

J. Jaya, K. Thanushkodi and M. Karnan, “Tracking Algorithm for De-Noising of MR Brain Images”, IJCSNS International Journal of Computer Science and Network Security, VOL.9 No.11, November 2009.

Jorge D. Mendiola-Santibaneza, Ivan R. Terol-Villalobosb, GilbertoHerrera-Ruiza and Antonio FernandezBouza, "Morphological Contrast Measure and Contrast Enhancement: One Application to the Segmentation of Brain MRI”, Elsevier, Signal Processing 87 (2007), 2125-2150. DOI: https://doi.org/10.1016/j.sigpro.2007.02.008

Sayali D. Gahukar, Dr. S.S. Salankar, “ Segmentation of MRI brain image using Fuzzy c-means for brain tumor diagnosis”, International Journal of Engineering Research and Applications, 2014, 4, 4 , 107-111.

Priyanka, Balwinder singh, A review on brain tumor detection using segmentation”, International journal of Computer Science and mobile computing, 2013, 2, 7, 48-54.

Anjum sheikh, R.K. Krishna, Subroto Dutt, “Energy efficient approach for segmentation of brain tumor using Ant colony optimization”, International Journal of computer technology and electronics engineering, 2011, 1, 3, 138-142.

T.D.Vishnumurthy, H.S. Mohana, A. Vaibhav , Meshram, “ Automatic segmentation of MRI mbrain images and Tumor detection using Morphological techniques”, International Conference on Electrical, Electronics, Communication, Computer and Optimization techniques, 2016, 6-11 DOI: https://doi.org/10.1109/ICEECCOT.2016.7955176

N. Senthilkumaran, R.Rajesh, “Brain image segmentation”, International journal of wisdom based computing, 2011, 1 (3), 14-18.

A. Meena, K.Raja, “Spatial Fuzzy C-Means PET Image Segmentation of NeurodegenerativeDisorder”, Indian Journal of Computer Science and Engineering (IJCSE), ISSN: 0976-5166 Vol. 4 No.1 Feb-Mar 2013, 50-55.

Sudip Kumar Adhikari,Jamuna Kanta Singb, Dipak Kumar Basub, Mita Nasipurib, “Conditional spatial fuzzy C-means clustering algorithmfor segmentation of MRI images”, Appl. Soft Comput. J. (2015), http://dx.doi.org/10.1016/j.asoc.2015.05.038. DOI: https://doi.org/10.1016/j.asoc.2015.05.038

Downloads

Published

2018-03-31

How to Cite

Devi, S., & Mano, A. (2018). AN EFFICIENT APPROACH FOR MR BRAIN IMAGE MULTILEVEL SEGMENTATION AND PERFORMANCE ANALYSIS . International Journal of Engineering Technologies and Management Research, 5(3), 230–233. https://doi.org/10.29121/ijetmr.v5.i3.2018.195