Automated Cervical cancer Segmentation using 3 Level Distcrete Wavelet Transform & ABC Algorithm

Authors(2) :-Annalakshmi Govindaraj, Dr. Ravi Subban

Cervical Cancer is one of the most dangerous diseases which threaten women all over the world, since it has no symptoms at the earlier stage. Hence automated cervical Image Segmentation aims in pre-learning or analysis of the cervical cancer without any surgical method. However this results in earlier detection and treatment of cervical cancer in women and saves life. This paper proposes a method for segmenting the nucleus of cervical cell by preprocessing using 3 level-DWT and segmenting by Artificial Bee colony Algorithm. For the experimental analysis, cervical cell images are used. The experimental results show the performance of the proposed system.

Authors and Affiliations

Annalakshmi Govindaraj
Department of CSE, Kamaraj College of Engineering and Technology, Virdhunagar, Tamilnadu, India
Dr. Ravi Subban
Department of Computer Science, School of Engineering and Technology, Central University, Pondicherry, India

Discrete Wavelet Transform, Artificial Bee Colony , cervical cancer, co-occurrence matrix, Grey Entropy.

  1. H. C. Kitchener, R. Blanks, G. Dunn, L. Gunn, M. Desai, R.  Albrow,  J. Mather,  D. N. Rana,  H. Cubie,  C. Moore,  R.Legood, A. Gray and S. Moss, Automation-assisted versus manual reading of cervical cytology (MAVARIC): a randomized controlled trial, The Lancet Oncology 12 (2011), 56-64.
  2. K. Li, Z. Lu, W. Liu, and J. Yin, "Cytoplasm and nucleus segmentation in cervical smear images using Radiating GVF Snake,” Pattern Recognit., 2012.
  3. C. Cengizler, M. Guven, and M. Avci, "A fluid dynamics-based deformable model for segmentation of cervical cell images,” Signal, Image Video Process., 2014.
  4. L. Zhang, H. Kong, C. T. Chin, S. Liu, T. Wang, and S. Chen, "Automated segmentation of abnormal cervical cells using global and local graph cuts," in Biomedical Imaging (ISBI), IEEE 11th International Symposium on , 2014.
  5. T. Chankong, N. Theera-Umpon, and S. Auephanwiriyakul, "Automatic cervical cell segmentation and classification in Pap smears.,” Computer methods and programs in biomedicine, vol. 113, no. 2, pp. 539-56, 2014.
  6. J. Oscanoa, M. Mena, and G. Kemper,"A detection method of ectocervical cell nuclei for pap test images based on adaptive thresholds and local derivatives,” International Journal of Multimedia and Ubiquitous Engineering, vol. 10, no. 2, pp.37-50,2015.
  7. K. Li, Z. Lu, W. Liu and J. Yin, Cytoplasm and  nucleus  segmentation in cervical smear  images   using Radiating GVF snake, Pattern Recognition 45 (2012), 1255-1264
  8. M. H. Tsai, Y. K. Chan, Z. Z. Lin, S. F. Yang-Mao and P. C. Huang, Nucleus and cytoplast contour detector of cervical smear image, Pattern Recognition Letters 29 (2008), 1441-1453
  9. T. Guan, D. Zhou, and Y. Liu, "Accurate Segmentation of Partially Overlapping Cervical Cells based on Dynamic Sparse Contour Searching and GVF Snake Model,”IEEE J. Biomed. Heal. Informatics, vol. 19, no. 4, pp. 2168-2194, 2015.
  10. Y. Song, L. Zhang, S. Chen, D. Ni, B. Lei, and T. Wang, "Accurate Segmentation of Cervical Cytoplasm and Nuclei Based on Multi-scale Convolutional Network and Graph Partitioning,” IEEE Trans. Biomed. Eng., 2015.
  11. Ming-Rung Tsai,1 Szu-Yu Chen,1 Dar-Bin Shieh,2,6 Pei-Jen Lou,3 and Chi-Kuang Sun1, "In vivo optical virtual biopsy of human oral mucosa with harmonic generation microscopy” Received 7 Apr 2011; revised 16 Jul 2011; accepted 20 Jul 2011; published 21 Jul 2011.
  12. Periklis Pantazis, Willy Supatto  "Advances in whole-embryo imaging: a quantitative transition is underway Nature Reviews Molecular Cell Biology”  15, 327-333 (2014) doi:10.1038/nrm3786  Published online 16 April 2014 .
  13. Miguel A Luengo-Oroz, Jose Rubio-Guivernau, Emmanuel Faure, Thierry Savy, Louise Duloquin, Nicolas Olivier, David Pastor, Maria Ledesma-Carbayo, Delphine Debarre, Paul Bourgine, Emmanuel Beaurepaire, Nadine Peyri´eras, Andres San "Methodology for reconstructing early zebrafish development from in-vivo multiphoton microscopy”JOURNAL OF LATEX CLASS FILES, VOL. 6, NO. 1, JANUARY 2007 .
  14. Miao Maa,b,, Jianhui Lianga, Min Guoa, Yi Fana, Yilong Yinb, "SAR image segmentation based on Artificial Bee Colony algorithm” Applied Soft Computing 11 (2011) 5205-5214
  15. Asl?Genc-tav , SevgenOnde "Unsupervised segmentation and classification of cervicalcellimages” Pattern Recognition 45 (2012) 4151-4168
  16. G.Zhu,S.Kwong,Gbest-guided  artificial eecolonyalgorithmfornumerical function optimization,Appl.Math.Comput.217(7)(2010)3166-3173.
  17. F.Kang J Li ZMa Rosenbrock artificial bee colony algorithm for accurate optimization for numerical functions Inf.Sci.181(16)(2011)3508-3531.
  18. A. Genctav, S. Aksoy, and S. Önder, "Unsupervised segmentation and classification of cervical cell images,” Pattern Recognit., 2012.

Publication Details

Published in : Volume 2 | Issue 6 | November-December 2017
Date of Publication : 2017-12-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 37-41
Manuscript Number : CSEIT172639
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Annalakshmi Govindaraj, Dr. Ravi Subban, "Automated Cervical cancer Segmentation using 3 Level Distcrete Wavelet Transform & ABC Algorithm", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 6, pp.37-41, November-December-2017.
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