Image Segmentation method based on Fuzzy Clustering: Application to MR Brain Tissue Extraction

By Hanane BARRAH, Abdeljabbar Cherkaoui


In this work, a fast and robust method for MR brain segmentation is proposed. This method is based on a fast and robust fuzzy clustering algorithm that is initialized close to the searched solution in order to speed up the segmentation process.  To validate the proposed method, we test it on some grayscale images and on a normal brain; brought from the BrainWeb Simulated Brain Database. The experimental results are important in both robustness to noise and running times standpoints.

Full Text:



D. L. Pham, C. Xu, et J. L. Prince, « Current methods in medical image segmentation 1 », Annu. Rev. Biomed. Eng., vol. 2, no 1, p. 315–337, 2000.

J. C. Bezdek, Fuzzy models and algorithms for pattern recognition and image processing. New York: Springer, 2005.

E. Abdel-Maksoud, M. Elmogy, et R. Al-Awadi, « Brain tumor segmentation based on a hybrid clustering technique », Egypt. Inform. J., vol. 16, no 1, p. 71‑81, mars 2015.

A. B. Hamza, P. L. Luque-Escamilla, J. Martínez-Aroza, et R. Román-Roldán, « Removing noise and preserving details with relaxed median filters », J. Math. Imaging Vis., vol. 11, no 2, p. 161–177, 1999.

D. Pham, « Spatial Models for Fuzzy Clustering », Comput. Vis. Image Underst., vol. 84, no 2, p. 285‑297, nov. 2001.

M. N. Ahmed, S. M. Yamany, N. Mohamed, A. A. Farag, et T. Moriarty, « A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data », Med. Imaging IEEE Trans. On, vol. 21, no 3, p. 193–199, 2002.

S. Chen et D. Zhang, « Robust Image Segmentation Using FCM With Spatial Constraints Based on New Kernel-Induced Distance Measure », IEEE Trans. Syst. Man Cybern. Part B Cybern., vol. 34, no 4, p. 1907‑1916, août 2004.

J. Wang, J. Kong, Y. Lu, M. Qi, et B. Zhang, « A modified FCM algorithm for MRI brain image segmentation using both local and non-local spatial constraints », Comput. Med. Imaging Graph., vol. 32, no 8, p. 685‑698, déc. 2008.

H. Barrah, A. Cherkaoui, et D. Sarsri, « Robust FCM Algorithm with Local and Gray Information for Image Segmentation », Adv. Fuzzy Syst., vol. 2016, p. 1‑10, 2016.

J.-L. Fan, W.-Z. Zhen, et W.-X. Xie, « Suppressed fuzzy c-means clustering algorithm », Pattern Recognit. Lett., vol. 24, no 9‑10, p. 1607‑1612, juin 2003.

L. Rokach et O. Maimon, « Clustering methods », in Data mining and knowledge discovery handbook, Springer, 2005, p. 321–352.

D. Lam et D. C. Wunsch, « Chapter 20 - Clustering », in Academic Press Library in Signal Processing, vol. Volume 1, J. A. K. S. Paulo S.R. Diniz Rama Chellappa and Sergios Theodoridis, Éd. Elsevier, 2014, p. 1115‑1149.

I. Ozkan et I. B. Turksen, « Upper and lower values for the level of fuzziness in FCM », Inf. Sci., vol. 177, no 23, p. 5143‑5152, déc. 2007.

L. Szilagyi, Z. Benyo, S. M. Szilágyi, et H. S. Adam, « MR brain image segmentation using an enhanced fuzzy c-means algorithm », in Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International Conference of the IEEE, 2003, vol. 1, p. 724–726.

J. Serra, « Introduction to mathematical morphology », Comput. Vis. Graph. Image Process., vol. 35, no 3, p. 283–305, 1986.

V. Ćurić, A. Landström, M. J. Thurley, et C. L. Luengo Hendriks, « Adaptive mathematical morphology – A survey of the field », Pattern Recognit. Lett., vol. 47, p. 18‑28, oct. 2014.

J. Serra, « Morphological filtering: An overview », Signal Process., vol. 38, no 1, p. 3‑11, 1994.

L. Vincent, « Morphological grayscale reconstruction in image analysis: applications and efficient algorithms », IEEE Trans. Image Process., vol. 2, no 2, p. 176–201, 1993.

S. M. Smith, « Fast robust automated brain extraction », Hum. Brain Mapp., vol. 17, no 3, p. 143–155, 2002.

D. Martin, C. Fowlkes, D. Tal, et J. Malik, « A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics », in Computer Vision, 2001. ICCV 2001. Proceedings. Eighth IEEE International Conference on, 2001, vol. 2, p. 416–423.

C. A. Cocosco, V. Kollokian, R. K.-S. Kwan, G. B. Pike, et A. C. Evans, « BrainWeb: Online Interface to a 3D MRI Simulated Brain Database », NeuroImage, vol. 5, p. 425, 1997.