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Brain MRI Segmentation based on Different Clustering Algorithms

by Enver Küçükkülahli, Pakize Erdoğmuş, Kemal Polat
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 155 - Number 3
Year of Publication: 2016
Authors: Enver Küçükkülahli, Pakize Erdoğmuş, Kemal Polat
10.5120/ijca2016912283

Enver Küçükkülahli, Pakize Erdoğmuş, Kemal Polat . Brain MRI Segmentation based on Different Clustering Algorithms. International Journal of Computer Applications. 155, 3 ( Dec 2016), 37-40. DOI=10.5120/ijca2016912283

@article{ 10.5120/ijca2016912283,
author = { Enver Küçükkülahli, Pakize Erdoğmuş, Kemal Polat },
title = { Brain MRI Segmentation based on Different Clustering Algorithms },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2016 },
volume = { 155 },
number = { 3 },
month = { Dec },
year = { 2016 },
issn = { 0975-8887 },
pages = { 37-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume155/number3/26589-2016912283/ },
doi = { 10.5120/ijca2016912283 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:00:19.896734+05:30
%A Enver Küçükkülahli
%A Pakize Erdoğmuş
%A Kemal Polat
%T Brain MRI Segmentation based on Different Clustering Algorithms
%J International Journal of Computer Applications
%@ 0975-8887
%V 155
%N 3
%P 37-40
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this study, MR Image segmentation has been realized with some clustering algorithms. In the study, the performances kmeans, lloyds, llyds-kmeans, pso clustering, ga clustering and jaya optimisation algorithms on some MR images from BRATS 2012 dataset have been compared. For the comparison, the manual segmentation results of MR images from BRATS 2012 dataset have been referenced and results have been compared with these referances. In the comparison RI (Rand Index), VOI (Variation of Information) and GCE (Global Consistency Error) have been used and results have been submitted. The results showed that the PSO algorithm yielded better results and has a better processing time than the other algorithms.

References
  1. Kasiri, K.; Dehghani, M.J.; Kazemi, K.; Helfroush, M.S.; Kafshgari, S., "Comparison evaluation of three brain MRI segmentation methods in software tools," in Biomedical Engineering (ICBME), 2010 17th Iranian Conference of , vol., no., pp.1-4, 3-4 Nov. 2010, J. O. and Abel, J. S., ``Bark and ERB Bilinear Trans¬forms'', IEEE Trans. Speech and Audio Proc., 7(6):697-708, 1999.
  2. Duraisamy, M.; Jane, F.M.M., "cellular neural network based medical image segmentation using artificial bee colony algorithm," in Green Computing Communication and Electrical Engineering (ICGCCEE), 2014 International Conference on , vol., no., pp.1-6, 6-8 March 2014
  3. Koley, S.; Majumder, A., "Brain MRI segmentation for tumor detection using cohesion based self merging algorithm," in Communication Software and Networks (ICCSN), 2011 IEEE 3rd International Conference on , vol., no., pp.781-785, 27-29 May 2011
  4. Rostami, M.T.; Ghasemi, J.; Ghaderi, R., "Neural network for enhancement of FCM based brain MRI segmentation," in Fuzzy Systems (IFSC), 2013 13th Iranian Conference on , vol., no., pp.1-4, 27-29 Aug. 2013
  5. Si, T.; De, A.; Bhattacharjee, A.K., "Brain MRI segmentation for tumor detection using Grammatical Swarm based clustering algorithm," in Circuit, Power and Computing Technologies (ICCPCT), 2014 International Conference on , vol., no., pp.1196-1201, 20-21 March 2014
  6. Alia, O.M.; Mandava, R.; Aziz, M.E., "A hybrid Harmony Search algorithm to MRI brain segmentation," in Cognitive Informatics (ICCI), 2010 9th IEEE International Conference on , vol., no., pp.712-721, 7-9 July 2010
  7. Hasanzadeh, M.; Kasaei, S., "Multispectral brain MRI segmentation using genetic fuzzy systems," in Signal Processing and Its Applications, 2007. ISSPA 2007. 9th International Symposium on , vol., no., pp.1-4, 12-15 Feb. 2007
  8. Jianwei Liu; Lei Guo, "A New Brain MRI Image Segmentation Strategy Based on K-means Clustering and SVM," in Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2015 7th International Conference on , vol.2, no., pp.270-273, 26-27 Aug. 2015
  9. Jianwei Liu; Lei Guo, "A new brain MRI image segmentation strategy based on wavelet transform and K-means clustering," in Signal Processing, Communications and Computing (ICSPCC), 2015 IEEE International Conference on , vol., no., pp.1-4, 19-22 Sept. 2015
  10. Sinha, K.; Sinha, G.R., "Efficient segmentation methods for tumor detection in MRI images," in Electrical, Electronics and Computer Science (SCEECS), 2014 IEEE Students' Conference on , vol., no., pp.1-6, 1-2 March 2014
  11. B. H. Menze et al., "The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)," in IEEE Transactions on Medical Imaging, vol. 34, no. 10, pp. 1993-2024, Oct. 2015.
  12. http://www2.imm.dtu.dk/projects/BRATS2012/
  13. Cabria, I.; Gondra, I., "Automated Localization of Brain Tumors in MRI Using Potential-K-Means Clustering Algorithm," in Computer and Robot Vision (CRV), 2015 12th Conference on , vol., no., pp.125-132, 3-5 June 2015
  14. Badmera, M.S.; Nilawar, A.P.; Karwankar, A.R., "Modified FCM approach for MR brain image segmentation," in Circuits, Power and Computing Technologies (ICCPCT), 2013 International Conference on , vol., no., pp.891-896, 20-21 March 2013
  15. Nguyen Duong Trung Dung; Huynh Thi Thanh Binh, "Using contour information for image segmentation," in Soft Computing and Pattern Recognition (SoCPaR), 2013 International Conference of , vol., no., pp.258-263, 15-18 Dec. 2013
  16. Xiaofang Wang; Yuxing Tang; Masnou, S.; Liming Chen, "A Global/Local Affinity Graph for Image Segmentation," in Image Processing, IEEE Transactions on , vol.24, no.4, pp.1399-1411, April 2015.
  17. Han, J., and Kamber, M., (2006), Data Mining Concepts and Techniques, Morgan Kauffmann Publishers Inc.
  18. AjalaFunmilola A, Oke O.A, Adedeji T.O, Alade O.M, Adewusi E.A, " Fuzzy k-c-means Clustering Algorithm for Medical Image Segmentation", Journal of Information Engineering and Applications, ISSN 2224-5782 (print) ISSN 2225-0506 (online) Vol 2, No.6, 2012.
  19. Greg Hamerly and Jonathan Drake. Accelerating Lloyds algorithm for k-means clustering. In Partitional Clustering Algorithms, pages 41{78. Springer, 2015.
  20. Kennedy, J., Eberhart, R., 1995, Particle Swarm Optimization, Proc. IEEE Intl. Conf. on Neural Networks, 1995 Perth Australia, Piscataway NJ: IEEE Service Center, 1942-1948.
  21. Eberhart, R., Shı, Y., 2001, Partical Swarm Optimization: Developments, Applications and Resources, Proc. IEEE Int'l Conf. on Evolutionary Computation, 2001 Seoul Korea, Piscataway, NJ: IEEE Service Center, 81-86.
  22. Rao R.V., 2016, Jaya: a simple and new optimization algorithm for solving constrained and unconstrained optimization problems, Int. J. Ind. Eng. Comput. 7 (1).
  23. Sathya, B., and R. Manavalan. "Image segmentation by clustering methods: performance analysis." International Journal of Computer Applications 29.11 (2011).
Index Terms

Computer Science
Information Sciences

Keywords

Kmeans particle swarm optimization genetic algorithm jaya optimization Lloyds

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