Abstract

References

[1] Aarthi R. , Divya K., Komala N. , and Kavitha S., Applica tion of Feature Extraction and C lustering in M ammogram Classification Using Support Vector Machine, Third International Conference on Advanced Computing (ICoAC) , India, pp. 62- 67, 2011.

[2] Amitava C. , Patrick S. , Amir N. , and Raphael B., An Improved B iogeography B ased Optimization A pproach for Segme ntation of H uman H ead CT -scan Employing Fuzzy Entropy, Engineering Applications of Artificial Intelligence , vol 25, no. 8, pp. 1698- 1709, 2012.

[ 3] An irban M. and Ujjwal M., A Multiobjective A pproach to MR B rain Image Segmentation, Applied Soft Computing, vol. 11, no.1, pp. 872- 880, 2011.

[ 4] Bing L., Chui C. , Chang S. , and Ong S., Integrating Spatial Fuzzy Clustering with L evel S et Methods for A utomated Medical Images Segmentat ion, computers in Biology and Medicine, vol. 41, no. 1, pp. 1- 10, 2011.

[ 5] Cui X., Palathingal P. , and Potok T., Document C lustering Using Particle Swarm Optimization, in Proceeding of IEEE Swarm Intelligenc e Symposium , pp. 185-191, 2005.

[ 6] Dao -Qiang Z. and Song -Can C., A N ovel K ernelized Fuzzy C -Means Algorithm with A pplication in Medical Image Segmentation, Artificial Intelligence in Medicine , vol. 32, no . 1, pp. 37- 50, 2004.

[ 7] Davies D . and Bouldin D ., A Cluster Separation M easure, IEEE Transaction on Pattern Analysis and Machine Intelligence , vol. 1, no. 2, pp. 224- 227, 1979.

[ 8] Fahd M ., Mohiy H., Kamel M., and Khalid A., A New Image Segmentation Met hod Based on Particle Swarm Optimization, The international Arab journal of Information Technology , vol. 9, no. 5, 2012.

[ 9] Gopal N . and Karnan M., Diagnose Brain T umor through MRI U sing Image Processing C lustering Algorithms Such as Fuzzy C Means A long wit h Intelligent Optimization T echniques, in Proceeding of IEEE International Conference on Computational Intelligence and Computing Research (ICCIC) , pp. 1- 4 , 2010.

[ 10] Haibo W ., Jing Z ., and Liwei W., Segmentation of Thoracic CT I mage Based on FCM C lustering , in Proceeding of Third International C onference on Advanced Computer Theory and Engineering (ICACTE) , pp. 405-408, 2010.

[ 11] Helen R. , Kamaraj N. , Selvi K. , and Raman V. , Segmentation of P ulmonary Parenchyma in CT L ung Images Based on 2D Otsu Optimized by PSO, in Proceeding of International Conference on Emerging Trends in Electrical and Computer Technology (ICETECT) , pp. 536-541, 2011.

[12] Jianchao F. , Min H. , and Jun W., Single P oint I terative Weighted Fuzzy C -means Clustering A lgorithm for Remote Sensing Image S egmentation, Pattern Recognition, vol . 42, no. 11, pp. 2527- 2540, 2009.

[ 13] Jie F. , Jiao L. , Xiangrong Z. , Maoguo G ., and Tao S., Robust N on-Local Fuzzy C-M eans A lgorithm with E dge Preservation for SAR I mage Segmentation, Signal Processing , vol. 93, no. 2, pp. 487- 499, 2013.

[ 14] Kannan S., Ramathilagam S. , Sathya A. , and Pandiyarajan R., Effective F uzzy C-M eans B ased Kernel Function in Segmenting Medical I mages, Computers in Biology and Medicine , vol. 40, no. 6, pp. 572- 579, 2010.

[ 15] Kennedy J. and Eberhart R., Particle S warm O ptimization, in Proceeding of IEEE International Conference On Neural Networks, NJ, pp. 1942- 1948, 1995.

[ 16] Neeraj S. and Lalit M. , Automated M edical I mage Segmentation Techniques, Journal of Medical Physics, vol. 35, no.1, pp. 3- 14, 2010.

[ 17] Pham T. , Eisenblatter U. , Golledge J., Baune B., and Berger K., Segmentation of Medical Images U sing Geo -T he oretic Distance Matrix in Fuzzy C lustering, in Proceeding of 16 th IEEE International Conference on Image Processing (ICIP) , pp. 3369- 3372, 2009.

[ 18] Prabhjot K., Soni A., and Anjana G., A Robust K ernelized Intuitionistic Fuzzy C-M eans C lustering Algorithm in S egmentation of N oisy M edical Images, Pattern Recognition Letters, vol. 34, no. 2, pp. 163- 175, 2013.

[ 19] Shen S. , Sandham W., Granat M., Dempsey M. , and Patterson J., Fuzzy Clustering Based A pplications to M edical Image Segmentation Engineering in Medicine and Biology Society, in Proc eedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society , pp. 747-750, 2003.

[ 20] Singh L. , Jaffery Z. , Zaheeruddin Z., and Singh R., Segmentation and Characterization of Breast Tumor in Mammograms, in Procee dings of International Conference on Advances in Recent Technologies in Communication and Computing (ARTCom) , pp. 213-216, 2010. 59 Medical Image Segmentation With Fuzzy C -Means and Kernelized Fuzzy C -Means Hybridized on

[21] Sun J., Feng B., and Xu W., Particle S warm O ptimization with Particles Having Quantum B ehavior, in Proceedings of the 2004 Congress on Evolutionary computation, pp. 325- 331, 2004.

[ 22] Sun J., Xu W., and Feng B., A G lobal Search S trategy of Q uantum-B ahaved Particle Swarm O ptimization, in Proceedings of IEEE Proceedings on Cybernetics and Intelligent Systems, pp.111 -116, 2004.

[ 23] Uric h K. , Simon H., and Klaus D., A Swarm Intelligence Inspired Algorithm for C ontour D etection in I mages, Applied Soft Computing, vol. 13, no. 6, pp. 3118- 3129, 2013.

[ 24] Weiling C. , Songcan C., and Daoqiang Z., A S imultaneous Learning Framework for C lustering and Classification, Pattern Recognition, vol. 42, no. 7, pp. 1248- 1259, 2009.

[ 25] Weiling C. , Songcan C., and Daoqiang Z., Fast and Robust Fuzzy C-M eans Clustering A lgorithms Incorporating Local Information for Im age Segmentation, Pattern Recognition, vol. 40, no. 3, pp. 825- 838, 2007.

[ 26] Yi L. and Xu C., The Application of W avelet M ultiresolution Technology in M edical Image A nalysis, in Proceedings of International Conference on Wavelet Analysis and Pattern Recognition, pp. 489- 493, 2007.

[ 27] Zanaty E., Determ ining the Number of C lusters for Kernelized Fuzzy C -M eans Algorithms for A utomatic Medical Image Segmentation, Egyptian Informati cs Journal, vol. 13, no. 1, pp. 39- 58, 2012.

[ 28] Zexuan J., Quansen S., Yong X., Qiang C., Deshen X. , and Dagan F., Generalized Rough F uzzy C-M eans Algorithm for B rain MR Image S egmentation, Computer Methods and Programs in Biomedicine , vol. 108, no. 2, pp. 644- 655, 2011.

[ 29] Zexuan J., Yong X., Qiang C., Quansen S., Deshen X. , and David F., Fuzzy C-M eans C lustering with Weighted Image Patch for Image S egmentation , Applied Soft Computing, vol. 12, no. 6, pp. 1659- 1667, 2012.

[ 30] Zhang D., and Chen S., A Novel Kernalized F uzzy C Means Algorithm with Application in M edical Image Segmentation, Artificial Intelligence in Medicine , vol. 32, no. 1, pp. 37- 50, 2004. Anu suya Venkatesan received her Master of Technology degree in 2005 from Manonmaniam Sundaranar University. Currently pursuing Ph.D in the discipline of Computer Science and Engineering from the same University. Her research interest includes clustering and c lassification of data sets, neural networks, image processing and computational intelligence. Latha Parthiban obtained her B.E deg ree from Madras University, M.E from Anna University and Ph.D from Pondicherry University. Her areas of interest include image processing, artificial neural networks, data mining, fuzzy logic and computational intelligence.