CFP last date
20 May 2024
Reseach Article

Analysis of Tumor Characteristics based on MCA Decomposition and Watershed Segmentation

by Narain Ponraj.d, Evangelin Jenifer.m, P. Poongodi, Samuel Manoharan.j
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 42 - Number 4
Year of Publication: 2012
Authors: Narain Ponraj.d, Evangelin Jenifer.m, P. Poongodi, Samuel Manoharan.j
10.5120/5678-7714

Narain Ponraj.d, Evangelin Jenifer.m, P. Poongodi, Samuel Manoharan.j . Analysis of Tumor Characteristics based on MCA Decomposition and Watershed Segmentation. International Journal of Computer Applications. 42, 4 ( March 2012), 1-6. DOI=10.5120/5678-7714

@article{ 10.5120/5678-7714,
author = { Narain Ponraj.d, Evangelin Jenifer.m, P. Poongodi, Samuel Manoharan.j },
title = { Analysis of Tumor Characteristics based on MCA Decomposition and Watershed Segmentation },
journal = { International Journal of Computer Applications },
issue_date = { March 2012 },
volume = { 42 },
number = { 4 },
month = { March },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume42/number4/5678-7714/ },
doi = { 10.5120/5678-7714 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:30:51.698213+05:30
%A Narain Ponraj.d
%A Evangelin Jenifer.m
%A P. Poongodi
%A Samuel Manoharan.j
%T Analysis of Tumor Characteristics based on MCA Decomposition and Watershed Segmentation
%J International Journal of Computer Applications
%@ 0975-8887
%V 42
%N 4
%P 1-6
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

An accurate and standardized technique for breast tumor segmentation is a critical step for monitoring and quantifying breast cancer. The fully automated tumor segmentation in mammograms presents many challenges related to characteristics of an image. In this paper, two different methods for mass detection are applied. First method uses morphological component analysis and multiple layer thresholding. Second method uses watershed segmentation. Features are extracted and the best one is found out for efficient identification of breast cancer.

References
  1. American Cancer Society. Breast cancer facts and figures 2007–2008.
  2. R. M. Rangayyan, F. J Ayres,et. al, july 2002. "A review of computer-aided diagnosis of breast cancer : Towards the detection of subtle signs", J. Franklin Inst. .
  3. Prof. Samir Kumar Bandyopadhyay, "Survey on Segmentation Methods for Locating Masses in a Mammogram Image", International Journal of Computer Applications,November 2010, Volume 9, No. 11.
  4. R. M. Rangayyan, L. shen, et. al, "Improvement of sensitivity of breast cancer diagnosis with adaptive neighbourhood contrast enhancement of mammograms", IEEE Trans. Med. Img, Sep 1997.
  5. D. Narain Ponraj, M. Evangelin Jenifer, Dr. P. Poongodi, J. Samuel Manoharan, "A Survey on the Preprocessing Techniques of Mammogram for the Detection of Breast Cancer", International Journal of Computer Science and Security (IJCSS), Volume (1), Issue (3), 2011.
  6. Xinbo Gao, Ying Wang, Xuelong Li, "On Combining Morphological Component Analysis and Concentric Morphology Model for Mammographic Mass Detection", IEEE transactions on information technology in biomedicine, march 2010, vol. 14, no. 2.
  7. S. K. Bandyopadhyay, "pre-processing of Mammogram Images", International Journal of Engineering Science and Technology, 2010, Vol. 2(11), pp 6753-6758.
  8. D. Narain ponraj, Sweety Kunjachan, Dr. P. Poongodi, Samuel manoharan, "A Survey on Texture analysis of mammogram for the detection of breast cancer", CIIT International journal, 2011, vol. 3.
  9. J. G. Schavemaker, M. J. Reinders, J. J. Gerbrands, and E. Backer, "Image sharpening by morphological filtering", Pattern Recognition, vol. 33, 2000,pp. 997–1012.
  10. Serra, J. 1982. Image Analysis and Mathematical Morphology, Academic Press, New York.
  11. Gonzalez RC, Woods R. E, 2003 Digital Image processing, 2nd ed.
  12. Shavi Gupta, Mohd. Sadiq, Mona Gupta and Naseem Rao. 2011. "Semi Automatic Segmentation of Breast Cancer for Mammograms Based on Watershed Segmentation", Proceedings of the 5th National Conference; INDIACom-2011.
  13. A. E. Hassanien and E. H. Tarek Abed,2003. "Digital Mammography Image Analysis System Based on Mathematical Morphology", in IEEE computer society 7th International Conference On Intelligent Engineering Systems INES ,Egypt, pg. 141-147.
  14. R. B. Dubey, M. Hanmandlu, S. K. Gupta, "A comparison of two methods for the segmentation of masses in the digital mammograms", Computerized Medical Imaging and Graphics 34,2010, pg. 185–191.
  15. H. S. Sheshadri and A. Kandaswamy, "Detection of Breast Cancer Tumor based on Morphological Watershed Algorithm", ICGST-GVIP Journal, May 2005 ,Volume (5), Issue (5).
  16. Vincent L, Soille P, "Watersheds in digital spaces: an efficient algorithm, based on immersion simulations", IEEE Trans Pattern Anal Mach Intell, 13(6), 1991, pg. 583–598.
  17. Jaya Sharma & Sujeet Sharma, "Mammogram image segmentation using watershed", International Journal of Information Technology and Knowledge Management, July-December 2011, Volume 4, No. 2, pg. 423-425.
  18. V. Grau, A. U. J. Mewes, M. Alcañiz, R. Kikinis, and S. K. Warfield, "Improved Watershed Transform for Medical Image Segmentation Using Prior Information", IEEE transactions on medical imaging,2004,vol. 23, no.
  19. J. Freixenet, X. Munoz, D. Raba, J. Marti, and X. Cufi ,2002. "Yet another survey on image segmentation, Region and boundary information integration", Computer Vision, pg. 408-422.
Index Terms

Computer Science
Information Sciences

Keywords

Breast Cancer Morphological Component Analysis Undecimated Wavelet Transform Watershed Segmentation