Analyzing ovarian tumor and cancer cells using image processing algorithms K means & fuzzy C-means

  • Authors

    • Thangamma N G
    • Dr S. Prasanna
    https://doi.org/10.14419/ijet.v7i2.33.14821

    Received date: June 30, 2018

    Accepted date: June 30, 2018

    Published date: June 8, 2018

  • Clustering, Image Processing Techniques, Ovarian Cancer, Segmentation

  • Abstract

    Ovarian growth is a tumor that occurs in the ovaries of the women. Sometimes, it may derive to be a malignant tumor. Those tumors are acute cancer cells that could be life-threatening if the treatment had not been properly taken. Few of the cases, malignant tumors can be re-moved using surgery or by means of radiations..There is a chance of cancer if not properly removed and they could grow back. Analyzing ovarian cancer is found to be the highest mortality rate of all categories of cancers affecting the women. Considering its malignant effect necessary remedial actions need to be carried out for the welfare of the peoples in the future. Researches and various analysis are being car-ried out to overcome the drastic effect of malignant tumor. Supporting the research, in this paper we have analyzed various imaging modali-ties to examine segmentation and texture analysis with the help of K-Means and Fuzzy C-Means.

  • References

    1. Dr. IoannisHatzipeteros, M.D,Novel Biomarkers In The Diagnosis Of Ovarian Cancer University of Pecs, Faculty of Medicine, Clini-cal Center Obstetrics and Gynecology Clinic Pecs, Hungary, 2014.
    2. Monica L. Andersen, Tathiana F. Alvarenga, RenataMazaro-Costa, Helena C. Hachul, Sergio Tufik, The association of testosterone, sleep, and sexual function in men and women, Brain Research, Vol-ume 1416, 6 October 2011, Pages 80-104.
    3. York, G. and Kim, Y. “Ultrasound Processing and Computing: Re-view and Future Directions”. Annual Review of Biomedical Engi-neering, vol.1, no.1, pp.559-581, 1999.
    4. Mahmood, N. H., Ahmmad, S. N. Z., Hashim, H. and Abdull-Rani, S. N. N. “Ovary Ultrasound Image Edge Detection Analysis: A Tu-torial using MATLAB”.International Journal of Engineering Re-search and Applications (IJERA), vol. 2, no. 3, pp.1635-1642, 2012.
    5. York, G. and Kim, Y. “Ultrasound Processing and Computing: Re-view and Future Directions”. Annual Review of Biomedical Engi-neering, vol.1, no.1, pp.559-581, 1999.
    6. Mahmood, N. H., Ahmmad, S. N. Z., Hashim, H. and Abdull-Rani, S. N. N. “Ovary Ultrasound Image EdgeDetection Analysis: A Tu-torial using MATLAB”.International Journal of Engineering Re-search and Applications (IJERA), vol. 2, no. 3, pp.1635-1642, 2012.
    7. Vause, T. D. R., Ottawa O. N., Cheung, A. P. and Vancouver, B. C. “Ovulation Induction in Polycystic Ovary Syndrome”. Journal of ObstetGynaecolCan,vol. 32, no. 5, pp.495–502, 2010.
    8. Ultrasound images of the Ovary. Retrieved from www.ultrasoundpaedia.com; www.ultrasoundimages.com; www.sonoworld.com, 20th, March 2015.
    9. Hamid, B. A. Image texture analysis of transvaginal ultrasound in monitoring ovarian cancer (Doctoral dissertation, School of Engi-neering, Cardiff University), pp.57-69, 2011.
    10. Bian, N., Eramian, M. G., and Pierson, R. A.“Evaluation of Texture Features for Analysis of Ovarian Follicular development”. Med Im-age ComputComput Assist Interv, pp.1-11, 2011.
    11. Vause, T. D. R., Ottawa O. N., Cheung, A. P. and Vancouver, B. C. “Ovulation Induction in Polycystic Ovary Syndrome”. Journal of ObstetGynaecolCan,vol. 32, no. 5, pp.495–502, 2010.
    12. Hamid, B. A. Image texture analysis of transvaginal ultrasound in monitoring ovarian cancer (Doctoral dissertation, School of Engi-neering, Cardiff University), pp.57-69, 2011.
    13. Bian, N., Eramian, M. G., and Pierson, R. A.“Evaluation of Texture Features for Analysis of Ovarian Follicular development”. Med Im-age ComputComput Assist Interv, pp.1-11, 2011.

  • Downloads

  • How to Cite

    N G, T., & S. Prasanna, D. (2018). Analyzing ovarian tumor and cancer cells using image processing algorithms K means & fuzzy C-means. International Journal of Engineering and Technology, 7(2.33), 510-512. https://doi.org/10.14419/ijet.v7i2.33.14821