Abstract
Brain image segmentation is one of the most important parts of clinical diagnostic tools. Fuzzy C-mean (FCM) is one of the most popular clustering based segmentation methods. In this paper, a review of the FCM based segmentation algorithms for brain MRI images is presented. The review covers algorithms for FCM based segmentation algorithms, their comparative evaluations based on reported results and the result of experiments for neighborhood based extensions for FCM.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Acton ST, Mukherjee DP (2000) Scale space classification using area morphology. IEEE Trans Image Process 9: 623–635
Ahmed MN, Yamany SM, Mohamed N, Farag AA, Moriarty T (2002) A modified fuzzy C-means algorithm for bias field estimation and segmentation of MRI data. IEEE Trans Med Imaging 21: 193–199
Bioimage suite: An integrated medical image analysis suite. URL: http://www.bioimagesuite.org
Balafar MA (2011a) Spatial based Expectation Maximizing (EM). Diagn Pathol 6:103
Balafar MA (2011b) New spatial based MRI image de-noising algorithm. Artif Intell Rev doi:10.1007/s10462-011-9268-0
Balafar MA, Ramli AR, Mashohor S (2011) Brain Magnetic resonance image segmentation using novel improvement for expectation maximizing. Neurosciences 16:242–247
Balafar MA, Ramli AR, Saripan MI, Mashohor S, Mahmud R (2010) Improved fast fuzzy C-mean and its application in medical image segmentation. J Circ Syst Comput 19: 203–214
Balafar MA, Ramli AR, Mashohor S (2010) A new method for MR grayscale inhomogeneity correction. Artif Intell Rev Springer 34: 195–204
Balafar MA, Ramli AR, Saripan MI, Mashohor S, Mahmud R (2010) Medical image segmentation using fuzzy C-mean (FCM) and user specified data. J Circ Syst Comput 19: 1–14
Balafar MA, Ramli AR, Saripan MI, Mahmud R, Mashohor S (2008) Medical image segmentation using anisotropic filter, user interaction and fuzzy C-mean (FCM). In: Communications in computer and information science. Springer, pp 169–176
Balafar MA, Ramli AR, Saripan MI, Mahmud R, Mashohor S (2008) Medical image segmentation using fuzzy C-mean (FCM), learning vector quantization (LVQ) and user interaction. In: Communications in computer and information science. Springer, pp 177–184
Boudouda H, Seridi H, Akdag H (2005) The fuzzy possibilistic C-means classifier. Asian J Inf Technol 4: 981–985
Balafar MA, Ramli AR, Saripan MI, Mashohor S (2010) Review of brain MRI image segmentation methods. Artif lntell Rev 33: 261–274
Balafar MA, Ramli AR, Mashohor S (2010) Compare different spatial based fuzzy C-mean (FCM) extensions for MRI image segmentation. Presented at ICCAE, pp 609–611
Balafar MA, Ramli AR, Mashohor S (2010) Edge-preserving clustering algorithms and their application for MRI image segmentation. Presented at IMECS, pp 17–19
Chen SC, Zhang DQ (2004) Robust image segmentation using FCM with spatial constraints based on new kernel-induced distance measure. IEEE Trans Syst Man Cybernet B 34: 1907–1916
Chuang K-S, Tzeng H-L, Chen S, Wu J, Chen T-J (2006) Fuzzy C-means clustering with spatial information for image segmentation. Comput Med Imaging Graph 30: 9–15
Cai W, Chen S, Zhang D (2007) Fast and robust fuzzy C-means clustering algorithms incorporating local information for image segmentation. Pattern Recognit 40: 825–838
Dave RN (1991) Characterization and detection of noise in clustering. Pattern Recognit Lett 12: 657–664
Hall LO, Bensaid AM, Clarke LP, Velthuizen RP, Silbiger MS, Bezdek JC (1992) A comparison of neural network and fuzzy clustering techniques insegmenting magnetic resonance images of the brain. IEEE Trans Neural Netw 3: 672–682
James CB (1981) Pattern recognition with fuzzy objective function algorithms. Kluwer, New York
Krishnapuram R, Keller JM (1993) A possibilistic approach to clustering. IEEE Trans Fuzzy Syst 1: 98–110
Karan Sikka NS, Singh PK, Mishra AK (2009) A fully automated algorithm under modified FCM framework for improved brain MR image segmentation. Magn Reson Imaging 27: 994–1004
Liew AWC, Leung SH, Lau WH (2000) Fuzzy image clustering incorporating spatial continuity. Inst Elec Eng Vis Image Signal Process 147: 185–192
Pham DL (2002) Fuzzy clustering with spatial constraints. In: Presented at IEEE proceedings of the international conference image processing, pp 65–68
Pham DL, Prince JL (1999) An adaptive fuzzy C-means algorithm for image segmentation in the presence of intensity inhomogeneities. Pattern Recognit Lett 20: 57–68
Smith SM, Jenkinson M, Woolrich MW, Beckmann CF, Behrens TE, Heidi Johansen-Berg PRB, et al. (2004) Advances in functional and structuralMR image analysis and implementation as FSL. NeuroImage 23: 208–19 URL: http://www.fmrib.ox.ac.uk/fsl
Shen S, Sandham W, Granat M, Sterr A (2005) MRI fuzzy segmentation of brain tissue using neighborhood attraction with neural-network optimization. IEEE Trans Inf Technol Biomed 9: 459–467
Szilágyi L, Benyó Z, Szilágyii SM, Adam HS (2003) MR brain image segmentation using an enhanced fuzzy C-means algorithm. Presented at 25th annual international conference of IEEE EMBS, pp 17–21
Tolias YA, Panas SM (1998) On applying spatial constraints in fuzzy image clustering using afuzzy rule-based system. IEEE Signal Process Lett 5: 245–247
Tolias YA, Panas SM (1998) Image segmentation by a fuzzy clustering algorithm using adaptive spatially constrained membership functions. IEEE Trans Syst Man Cybernet A 28: 359–369
Wang J, Kong J, Lub Y, Qi M, Zhang B (2008) A modified FCM algorithm for MRI brain image segmentation using both local and non-local spatial constraints. Computerized medical imaging and graphics. doi:10.1016/j.compmedimag.2008.08.004
Yong Y, Chongxun Z, Pan L (2004) A novel fuzzy C-means clustering algorithm for image thresholding. Meas Sci Rev 4: 11–19
Zhang DQ, Chen SC (2004) A novel kernelized fuzzy C-means algorithm with application in medical image segmentation. Artif Intell Med 32: 37–50
Zou K, Wang Z, Hu M (2008) An new initialization method for fuzzy C-means algorithm. Fuzzy Opt Decis Making 7: 409–416