Hybrid self organizing map for improved implementation of brain MRI segmentation

2010 International Conference on Signal Acquisition and Processing, ICSAP 2010

Volumn , Issue , 2010, Pages 248-252

  Logeswari, T ^a   Karnan, M ^b  

^a MOTHER TERESA WOMEN S UNIVERSITY   (India)

^b Tamilnadu College of Engineering   (India)

Author keywords

Fuzzy c mean; HSOM; Image analysis; Segmentation; Tumor detection

Indexed keywords

BRAIN IMAGES; BRAIN MRI; CLUSTERING METHODS; FUZZY C-MEAN; FUZZY C-MEAN CLUSTERING ALGORITHM; IMAGE VOLUME; MEDICAL IMAGE SEGMENTATION; MR IMAGES; SECOND PHASE; SEGMENTATION METHODS; TISSUE STRUCTURE; TUMOR DETECTION; TWO PHASIS;

CLUSTERING ALGORITHMS; DIGITAL IMAGE STORAGE; IMAGE ANALYSIS; SELF ORGANIZING MAPS; SIGNAL ANALYSIS; SIGNAL DETECTION; SIGNAL PROCESSING; TUMORS;

IMAGE SEGMENTATION;

EID: 77952214696     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICSAP.2010.56     Document Type: Conference Paper

References (23)

1. Aaron Lefohn, Joshua Cates, Ross Whitaker,:"Interactive GPU-Based level sets for 3D Brain Tumor Segmentation",April 16,2003
2. Ahalt, S.C., A.K. Krishnamurthy, P. Chen and D.E.Melton, 1990. "Competitive learning algorithms for Vector quantization", Neural Networks 3 (3): 277-329
3. Alirezaie, J., M.E. Jernigan and C. Nahmias, 1997."Neural Network based segmentation of MagneticResonance Images of the Brain", IEEE Trans. Nuclear Science, 44 (2): 194-198 (Pubitemid 127762132)
4. Dunn, J.C., 1973." A fuzzy relative of the ISODATA process and its use in detecting compact, well Separated clusters",JournalofCybernetics, 3: 32-115
5. Fu, K.S. and J.K. Mui, 1981." A survey on image segmentation", Pattern ecognition, 13: 3-16
6. Fadi N.Karameh, Munther A.Dahleh,:" Automated Classification of EEG signals in brain tumor diagnostics",Proceedings of the American Control Conference Chicago, IIIinois, June 2000
7. Haralick, R.M. and L.G. Shapiro, 1985. "Survey ,imagesegmentation techniques", Computer Vision, Graphics Image Process, 29: 100-132[9]
8. hanShen,WilliamSandham,MalcolmGranet,Annette Sterr.:"MRI Fuzzy Segmentation of Brain Tissue Using Neighbourhood Attraction with Neural-Network Optimization",IEEE Transcations on Information Technology in BiomedicineVol.9,No.3,Sep 2005
9. Kohonen, T., 1988. "Self-Organization and Associative Memory", 2nd Edition (Springer-Verlag, Berlin, Germany
10. Mahamed, N.A., M.N. Ahmed and A. Farag, "Modified fuzzy c-mean in medical image Segmentation", in Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Pocessing, Piscataway, NJUSA,6: 3429-3432
11. Lin, W., E. Tsao and C. Chen, 1991. "Constraint satisfaction neural networks for image segmentation", In: T.Kohonen, K. Mkisara, 0. Simula and J. Kangas (eds.), Artificial Neural Networks (Elsevier Science Publishers), pp: 1087-1090
12. M. Karnan, R. Sivakumar, M. Almelumangai, K. Selvanayagi and T. Logeswari," Hybrid ParticleSwarm Optimization for Automatically Detect the Breast Border and Nipple position toIdentify the Suspicious Regions on Digital Mammograms Based on Asymmetries",International Journal of Soft Computing 3 (3): 220-223, 2008
13. Parra, C.A., K. Iftekharuddin and R. Kozma, 2003."Automated Brain Tumor segmentation and pattern recognition using ANN", Computational Intelligence Robotics and Autonomous Systems
14. Rahmi, S., M. Zargham, A. Thakre and D.Chhillar,2004. "A Parallel Fuzzy C-Mean Algorithm for Image segmentation Fuzzy information", processing NAFIPS 04, IEEE Annual meeting, 1: 234-237
15. R.D Pascal-Marqui, A.D. Pascual Montano, K. Kochi, and J.M. Carazo. "Smoothly distributed fuzzy ca new self organizing map". Pattern Recognition,(34):2395-2402, 2001
16. Sahoo, P.K., S. Soltani, A.K.C. Wong and Y.C. Chen, 1988. "A survey of thresholding techniques", Computer Vision, Graphics Image Process. 41: 233-260
17. Siyal M.Y,Lin yu,:"An Intelligent modified fuzzy C-means based algorithm for bias estimation and Segmentation of brain MRI",Elsevier, Pattern Recognition Letters,26,2005
18. Siyal M.Y,Lin yu,:"An Intelligent modified fuzzy C-means based algorithm for bias estimation and Segmentation of brain MRI",Elsevier, Pattern Recognition Letters,26,2005
19. Scherf, A. and G. Roberts, 1990. "Segmentation using neural networks for automatic thresholding", in: S. Rogers (ed.), Proc. SPlE Conference on Applications of Artificial Neural Networks (Orlando, FL, 1294), pp: 118-124
20. S. Murugavalli1 , V. Rajamani," An Improved Implementation of Brain Tumor Detection Using Segmentation Based on Neuro Fuzzy Technique" Journal of Computer Science 3 (11): 841-846, 2007
21. S. Murugavalli1 , V. Rajamani," "A high speed parallel fuzzy c-mean algorithm for brain tumor segmentation", BIME Journal, Volume (06), Issue (1), Dec., 2006
22. K.Thangavel, M.Karnan, R.Sivakumar and A.Kaja Mohideen "Computer Aided Diagnosis in Digital Mammograms: Hybrid Meta-Heuristic Algorithms" GVIP Journal, Volume 5, Issue 7, July 2005
23. K.Thangavel, M.Karnan, "CAD System for Preprocessing and Enhancement Of Digital Mammograms" GVIP Journal, Volume 5, Issue 9, Dec. 2005