CFP last date
20 May 2024
Reseach Article

Medical Image Segmentation by Evolutionary Approach and Watershed Morphology

by Ahmad El Allaoui, M’barek Nasri
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 47 - Number 24
Year of Publication: 2012
Authors: Ahmad El Allaoui, M’barek Nasri
10.5120/7505-0616

Ahmad El Allaoui, M’barek Nasri . Medical Image Segmentation by Evolutionary Approach and Watershed Morphology. International Journal of Computer Applications. 47, 24 ( June 2012), 24-28. DOI=10.5120/7505-0616

@article{ 10.5120/7505-0616,
author = { Ahmad El Allaoui, M’barek Nasri },
title = { Medical Image Segmentation by Evolutionary Approach and Watershed Morphology },
journal = { International Journal of Computer Applications },
issue_date = { June 2012 },
volume = { 47 },
number = { 24 },
month = { June },
year = { 2012 },
issn = { 0975-8887 },
pages = { 24-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume47/number24/7505-0616/ },
doi = { 10.5120/7505-0616 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:42:43.326151+05:30
%A Ahmad El Allaoui
%A M’barek Nasri
%T Medical Image Segmentation by Evolutionary Approach and Watershed Morphology
%J International Journal of Computer Applications
%@ 0975-8887
%V 47
%N 24
%P 24-28
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Segmentation by watershed transform is a fast, robust and widely used in image processing and analysis, but it suffers from over-segmentation. We present in this paper some improvements to this algorithm based on the evolutionary algorithm and mathematical morphology in order to get over this difficulty. The performance of this method is validated on medical images. The results obtained show the good performance of this approach.

References
  1. S. Beucher, Unbiased Implementation of the Watershed Transformation based on Hierarchical Queues. CMM Internal note, Paris 206 School of Mines, 2004.
  2. S. Beucher. Watershed, hierarchical segmentation and waterfall algorithm. Mathematical morphology and its applications to image processing, pages 69–76. Kluwer Academic Publishers, 1994.
  3. M. Ali HAMDI. Modified Algorithm marker-controlled watershed transform for Image segmentation Based on Curvelet Threshold. Canadian Journal on Image Processing and Computer Vision. pp, 88-91. Vol. 2 No. 8, December 2011.
  4. J. Serra, Image Analysis and Mathematical Morphology. Academic Press, London 1982.
  5. R. C. Gonzalez and R. E. Woods, Digital Image Processing, Prentice-Hall, Upper Saddle River, NJ, USA, 2nd edition, 2002.
  6. Vincent, L. , "Morphological Grayscale Reconstruction in Image Analysis: Applications and Efficient Algorithms," IEEE Transactions on Image Processing, Vol. 2, No. 2, pp. 176-201, April, 1993.
  7. Sarah Ghandour. Segmentation d'images couleurs par morphologie mathématique : application aux images microscopiques. Thèse doctorat, Université Paul Sabatier, Toulouse 12 Juillet 2010.
  8. P. Arbeláez and L. Cohen. Constrained image segmentation from hierarchical boundaries. CVPR, 2008.
  9. P. Arbeláez, M. Maire, C. Fowlkes and J. Malik. Contour Detection and Hierarchical Image Segmentation IEEE TPAMI, Vol. 33, No. 5, pp. 898-916, May 2011.
  10. K. Parvati, et al, Image Segmentation Using Gray-Scale Morphology and Marker-Controlled Watershed Transformation. Discrete Dynamics in Nature and Society, vol. 2008, Article ID 384346, 8 pages, 2008.
  11. S. Lefèvres. Segmentation par Ligne de Partage des Eaux avec Marqueurs Spatiaux et Spectraux. XXIIe colloque GRETSI (traitement du signal et des images), Dijon (FRA), 8-11 septembre 2009.
  12. V. Letournel. Contribution à l'évaluation d'algorithmes de traitement d'images. Thèse de Doctorat de l'ENST. 2002.
  13. S. Philipp-Foliguet. Evaluation de la segmentation. Rapport Technique, 2001.
  14. C. Rosenberger, S. Chabrier, H. Laurent, B. Emile. Unsupervised and supervised image segmentation evaluation. Chapitre 18, pages 365-393 du livre Advances in Image and Video Segmentation, Pr. Yu-Jin Zhang, Idea Group Publishing, 2006.
  15. J. Brunette, R. Mongrain et G. Cloutier. A novel realistic three-layer phantom for intravascular ultrasound imaging. International Journal Cardiac Imaging, 17(5),pp 371- 381 (2001).
  16. M. Nasri. Contribution à la classification de données par Approches Evolutionnistes : Simulation et application aux images de textures. Thèse de doctorat. Université Mohammed premier Oujda 2004.
  17. J. M. Renders. Algorithmes génétiques et Réseaux de Neurones. Editions HERMES, 1995.
  18. A. EL Allaoui, M. Merzougui, M. Nasri, M. EL Hitmy and H. Ouariachi. Evolutionary Image Segmentation By Pixel Classification Application To Medical Images. IJCIIS International Journal of Computational Intelligence and Information Security, ISSN: 1837-7823, Vol. 2, No. 3 pp. 12-24. March 2011.
  19. A. EL Allaoui, M. Nasri, M. Merzougui , M. EL Hitmy et B. Bouali. Medical Image Segmentation By Region Evolutionary Approach. The 3rd International Conference on Multimedia Computing and Systems ICMCS'12 Tangier, CDROM, 10-12 Mai 2012.
Index Terms

Computer Science
Information Sciences

Keywords

Image Processing Medical Image Segmentation Watershed Evolutionary Algorithm Dilatation Mathematical Morphology