New robust fuzzy c-means based gaussian function in classifying brain tissue regions

Communications in Computer and Information Science

Volumn 40, Issue , 2009, Pages 158-169

  Kannan, S R ^a,b   Sathya, A ^b   Ramathilagam, S ^a   Pandiyarajan, R ^b  

^a NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

^b GANDHIGRAM RURAL UNIVERSITY   (India)

Author keywords

Clustering; Fuzzy C Means; Gaussian Function; Image Segmentation; Kernel Function; MR Imaging

Indexed keywords

CLUSTERING; FUZZY C MEAN; GAUSSIAN FUNCTION; KERNEL FUNCTION; MR IMAGING;

FUZZY CLUSTERING; FUZZY SYSTEMS; GAUSSIAN DISTRIBUTION; MAGNETIC RESONANCE IMAGING; MEDICAL IMAGING;

IMAGE SEGMENTATION;

EID: 70349934231     PISSN: 18650929     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-03547-0_16     Document Type: Conference Paper

References (26)

1. Ahmed, M.N., Yamany, S.M., Mohamed, N., Farag, A.A., Moriarty, T.: A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data. IEEE Trans. on Medical Imaging 21, 193-199 (2002)
2. Al-Sultan, K.S., Selim, S.Z.: A Global Algorithm for the Fuzzy Clustering Problem. Pattern Recognition 26(9), 1357-1361 (1993)
3. Al-Sultan, K.S., Fedjki, C.A.: A Tabu Search-based Algorithm for the Fuzzy Clustering Problem. Pattern Recognition 30(12), 2023-2030 (1997)
4. Bezdek, J.C.: Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum Press, New York (1981)
5. Bezdek, J.C., Pal, S.K. (eds.): Fuzzy Models for Pattern Recognition. IEEE Press, New York (1992)
6. Bezdek, J.C., Hall, L.O., Clarke, L.P.: Review of MR image segmentation techniques using pattern recognition. Med. Phys. 20, 1033-1048 (1993)
7. Brand, M.E., Bohan, T.P., Kramer, L.A.: Estimation of CSF and gray matter volumes in hydrocephalic children using fuzzy clustering of MR images. Comput. Med. Imaging Graph. 18, 25-34 (1994)
8. Carvalho, B.M., Gau, J.C., Herman, G.T., Kong, Y.: Algorithms for Fuzzy Segmentation. Pattern Analysis & Applications 2(1), 73-81 (1999)
9. Clark, M.C., Hall, L.O., Goldgof, D.B., Velthuizen, R., Murtagh, F.R., Silbiger, M.S.: Automatic tumor-segmentation using knowledge-based techniques. IEEE Transactions on Medical Imaging 117, 187-201 (1998)
10. Dunn, J.C.: A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters. Journal of Cybernetics 3, 32-57 (1973)
11. Fletcher-Heath, L.M., Hall, L.O., Goldgof, D.B., Murtagh, F.R.: Automatic segmentation of non-enhancing brain tumors in magnetic resonance images. Artifical Intelligence in Medicine 21, 43-63 (2001)
12. Gering, D.T., Grimson, W.E.L., Kikinis, R.: Recognizing deviations from normalcy for brain tumor segmentation. In: Dohi, T., Kikinis, R. (eds.) MICCAI 2002. LNCS, vol.2488, pp. 388-395. Springer, Heidelberg (2002)
13. Hall, L.O., Bensaid, A.M., Clarke, L.P., Velthuizen, R.P., Silbiger, M.S., Bezdek, J.C.: A Comparison of Neural Network and Fuzzy Clustering Techniques in Segmenting Magnetic Resonance Images of the Brain. IEEE Trans. Neural Networks. 3(5), 672-682 (1992)
14. Xue, J.-H., Pizurica, A., Philips, W., Kerre, E., Walle, R.V., Lemahieu, I.: An Integrated Method of Adaptive Enhancement for Unsupervised Segmentation of MRI Brain Images. Pattern Recognition Letters 24(15), 2549-2560 (2003)
15. Krishnan, N., Nelson Kennedy Babu, C.V., Joseph Rajapandian, V., Richard Devaraj, N.: A Fuzzy Image Segmentation using Feedforward Neural Networks with Supervised Learning. In: Proceedings of the International Conference on Cognition and Recognition, pp. 396-402
16. Kwon, M.J., Han, Y.J., Shin, I.H., Park, H.W.: Hierarchical fuzzy segmentation of brain MR images. Int. J. Imaging Systems and Technology. 13, 115-125 (2003)
17. Li, X., Li, L., Lu, H., Chen, D., Liang, Z.: Inhomogeneity correction for magnetic resonance images with fuzzy C-mean algorithm. In: Proc. SPIE, vol.5032, pp. 995-1005 (2003)
18. Li, C.L., Goldgof, D.B., Hall, L.O.: Knowledge-based classification and tissue labeling of MR images of human brain. IEEE Trans. Med. Imag. 12(4), 740-750 (1993)
19. Liew, A.W.C., Leung, S.H., Lau, W.H.: Fuzzy image clustering incorporating spatial continuity. IEE Proc. Visual Image Signal Process. 147, 185-192 (2000)
20. Clark, M.C., Hall, L.O., Goldgof, D.B., Clarke, L.P., Velthuizen, R.P., Silbigger, M.S.: MRI Segmentation using fuzzy clustering Techniques. IEEE Engineering in Medicine and Biology 13(5), 730-742 (1994)
21. Moussaoui, A., Benmahammed, K., Ferahta, N., Chen, V.: A New MR Brain Image Segmentation Using an Optimal Semisupervised Fuzzy C-means and pdf Estimation. Electronic Letters on Computer Vision and Image Analysis 5(4), 1-11 (2005)
22. Noordam, J.C., van den Broek, W.H.A.M., Buydens, L.M.C.: Geometrically guided fuzzy C-means clustering for multivariate image segmentation. In: Proc. Int. Conf. on Pattern Recognition, vol.1, pp. 462-465 (2000)
23. Pham, D.L., Prince, J.L.: Adaptive fuzzy segmentation of magnetic resonance images. IEEE Trans. Medical Imaging. 18, 737-752 (1999)
24. Runkler, T.A., Bezdek, J.C.: Alternating cluster estimation: A new tool for clustering and function approximation. IEEE Trans. on Fuzzy Systems. 7(4), 377-393 (1999)
25. Ruspini, E.H.: A New Approach to Clustering. Information and Control 15(1), 22-32 (1969)
26. Ruspini, E.H.: Numerical methods for fuzzy clustering. Inform. Sci. 2, 319-350 (1970)