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Reseach Article

Comparison of F-Measure, BER and PSNR of Tumor Detection using Hybridization of Fuzzy and Region Growing

by Simran Arora, Gurjit Singh, V.K. Banga
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 124 - Number 3
Year of Publication: 2015
Authors: Simran Arora, Gurjit Singh, V.K. Banga
10.5120/ijca2015905159

Simran Arora, Gurjit Singh, V.K. Banga . Comparison of F-Measure, BER and PSNR of Tumor Detection using Hybridization of Fuzzy and Region Growing. International Journal of Computer Applications. 124, 3 ( August 2015), 32-38. DOI=10.5120/ijca2015905159

@article{ 10.5120/ijca2015905159,
author = { Simran Arora, Gurjit Singh, V.K. Banga },
title = { Comparison of F-Measure, BER and PSNR of Tumor Detection using Hybridization of Fuzzy and Region Growing },
journal = { International Journal of Computer Applications },
issue_date = { August 2015 },
volume = { 124 },
number = { 3 },
month = { August },
year = { 2015 },
issn = { 0975-8887 },
pages = { 32-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume124/number3/22086-2015905159/ },
doi = { 10.5120/ijca2015905159 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:13:26.205298+05:30
%A Simran Arora
%A Gurjit Singh
%A V.K. Banga
%T Comparison of F-Measure, BER and PSNR of Tumor Detection using Hybridization of Fuzzy and Region Growing
%J International Journal of Computer Applications
%@ 0975-8887
%V 124
%N 3
%P 32-38
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper has dedicated to brain tumor detection algorithm. The majority of the existing work with tumor detection has neglected the using object-based segmentation. Thus this paper has planned an effective brain tumor detection using the feature detection and roundness metric. To boost the tumor detection rate further we've incorporated the proposed hybridization of fuzzy C-means and region growing segmentation based tumor detection with the use of trilateral filter in its preprocessing stage. The planned method has the capability to generate efficient results even in the event of large occurrence of the noise. The experimental results have obviously shown that the planned method outperforms over the available techniques.

References
  1. Abdel-Maksoud,Eman,Mohammed Elmogy and Rashid Al-Awadi. "Brain tumor segmentation based on a hybrid clustering technique." Egyptian Informatics Journal (2015).
  2. Perumal, K., and V. G. Karthikram. "A Fusion of SOM and Fuzzy C-Means for Image Processing." International Journal of Computer Technology and Applications 4.4 (2013): 647.
  3. Jose, Alan, S. Ravi, and M. Sambath. "Brain Tumor Segmentation Using K-Means Clustering And Fuzzy C-Means Algorithms And Its Area Calculation."Brain 2.3 (2014).
  4. Dou, W., Ruan, S., Chen, Y., Bloyet, D., and Constans, J. M. (2007), “A framework of fuzzy information fusion for segmentation of brain tumor tissues on MR images”, Image and Vision Computing, 25:164–171.
  5. Roy, Sudipta, and Samir K. Bandyopadhyay. "Detection and Quantification of Brain Tumor from MRI of Brain and it’s Symmetric Analysis." International Journal of Information and Communication Technology Research 2.6 (2012).
  6. Acharya J, Gadhiya S, Raviya. Segmentation techniques for image analysis: a review. Int J Comput Sci Manage Res 2013;2(4):1218–21.
  7. Naik D, Shah P. A review on image segmentation clustering algorithms. Int J Comput Sci Inform Technol 2014;5(3):3289–93.
  8. Christe SA, Malathy K, Kandaswamy A. Improved hybrid segmentation of brain MRI tissue and tumor using statistical features. ICTACT J Image Video Process 2010;1(1):34–49.
  9. Seerha GK, Kaur R. Review on recent image segmentation techniques. Int J Comput Sci Eng (IJCSE) 2013;5(2):109–12.
  10. Abdel-Maksoud,Eman,Mohammed Elmogy and Rashid Al-Awadi. "Brain tumor segmentation based on a hybrid clustering technique." Egyptian Informatics Journal (2015).
  11. Havaei, Mohammad, P-M. Jodoin, and Hugo Larochelle. "Efficient interactive brain tumor segmentation as within-brain kNN classification." Pattern Recognition (ICPR), 2014 22nd International Conference on. IEEE, 2014.
  12. Preetha, R., and G. R. Suresh. "Performance Analysis of Fuzzy C Means Algorithm in Automated Detection of Brain Tumor." Computing and Communication Technologies (WCCCT), 2014 World Congress on. IEEE, 2014.
  13. Dhanalakshmi, P., and T. Kanimozhi. "Automatic segmentation of brain tumor using K-Means clustering and its area calculation." International Journal of advanced electrical and Electronics Engineering 2.2 (2013): 130-134.
  14. Kumar, E. Praveen, V. Manoj Kumar, and M. G. Sumithra. "Tumour detection in brain MRI using improved segmentation algorithm." Computing, Communications and Networking Technologies (ICCCNT), 2013 Fourth International Conference on. IEEE, 2013.
  15. N. Albert Singh, "Detection of brain tumor using neural network", ICCCNT, 2013, 2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT), 2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT) 2013, pp. 1-5, doi:10.1109/ICCCNT.2013.6726524
  16. S. Parisot, "Graph-based detection, segmentation & characterization of brain tumors", CVPR, 2012, 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013 IEEE Conference on Computer Vision and Pattern Recognition 2012, pp. 988-995, doi:10.1109/CVPR.2012.6247775
  17. Bhattacharjee, Rupsa, and Monisha Chakraborty. "Brain tumor detection from MR images: Image processing, slicing and PCA based reconstruction."Emerging Applications of Information Technology (EAIT), 2012 Third International Conference on. IEEE, 2012.
  18. Shasidhar, M., V. Sudheer Raja, and B. Vijay Kumar. "MRI brain image segmentation using modified fuzzy c-means clustering algorithm."Communication Systems and Network Technologies (CSNT), 2011 International Conference on. IEEE, 2011.
  19. Bhat, Subramanya, and Sanjeev R. Kunte. "A mixed model based on Watershed and Active contour algorithms for brain tumor segmentation."Advances in Recent Technologies in Communication and Computing (ARTCom), 2010 International Conference on. IEEE, 2010.
  20. Kannan, S. R., and R. Pandiyarajan. "Effective fuzzy c-mean clustering technique for segmentation of T1-T2 brain MRI." Advances in Recent Technologies in Communication and Computing, 2009. ARTCom'09. International Conference on. IEEE, 2009.
  21. Singh, Laxman, R. B. Dubey, and Z. A. Jaffery. "Segmentation and characterization of brain tumor from MR images." Advances in Recent Technologies in Communication and Computing, 2009. ARTCom'09. International Conference on. IEEE, 2009.
  22. Wu, Ming-Ni, Chia-Chen Lin, and Chin-Chen Chang. "Brain tumor detection using color-based k-means clustering segmentation." Intelligent Information Hiding and Multimedia Signal Processing, 2007. IIHMSP 2007. Third International Conference on. Vol. 2. IEEE, 2007.
  23. Mohan P, AL V, Devi BRS, Kavitha BC. Intelligent based brain tumor detection using ACO. Int J Innovat Res Comput Commun Eng 2013;1(9):2143–50.
  24. Anandgaonkar G, Sable G. Brain tumor detection and identification from T1 post contrast MR images using cluster based segmentation. Int J Sci Res 2014;3(4):814
  25. Jude hemanth.D, D.Selvathi and J.Anitha,“Effective Fuzzy Clustering Algorithm for Abnormal MR Brain Image Segmentation”,Page Number609-614, International/Advance Computing Conference (IACC2009),IEEE,2009
  26. Sorin Istrail, “An Overview of Clustering Methods”, With Applications to Bioinformatics.
  27. Steven Eschrich, Jingwei Ke, Lawrence O. Hall and Dmitry B. Goldgof Fast “Accurate Fuzzy Clustering through Data Reduction”, Page Number 1-18,November 13 IEEE 2002..
  28. Vasuda, P., and S. Satheesh. "Improved fuzzy C-means algorithm for MR brain image segmentation." International Journal on Computer Science and Engineering 2.5 (1713): 2010.
  29. Issac N. Bankman, “Handbook of medical image processing and analysis”, Second edition, Academic press, USA, 2008.
Index Terms

Computer Science
Information Sciences

Keywords

Brain Tumor Segmentation Fuzzy C-means Region growing Trilateral filter.