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IJML 2012 Vol.2(1): 7-12
doi: 10.7763/IJMLC.2012.V2.81

GUI Based Automatic Breast Cancer Mass and Calcification Detection in Mammogram Images using K-means and Fuzzy C-means Methods

Nalini Singh , Ambarish G Mohapatra , Biranchi Narayan Rath , Guru Kalyan Kanungo

  • Silicon Institute of Technology, Silicon Hills, Patia, Bhubaneswar-751024, India.

Abstract

Mammogram breast cancer images have the ability to assist physicians in detecting brest cancer caused by cells abnormal growth.The first step of the cancer signs detection should be a segmentation procedure able to distinguish masses and micro calcifications from background tissue. This study is an attempt to reduce false alarm in Breast cancer detection. This paper presents a research on mammography images using K-means and Fuzzy C – means clustering for detecting cancer tumor mass and micro calcification. The proposed technique shows better results in less time (in Seconds) and user friendly as it is based on Graphical User Interfaces(GUI). The real time implementation of the proposed method can be implemented using data acquisition hardware and software interface with the mammography systems.

Keywords

  • Clustering
  • Fuzzy C–means
  • GUI
  • K-means
  • Mammography
  • Segmentation
81-A1039

How to Cite

Copied

Nalini Singh, Ambarish G Mohapatra, Biranchi Narayan Rath, and Guru Kalyan Kanungo, "GUI Based Automatic Breast Cancer Mass and Calcification Detection in Mammogram Images using K-means and Fuzzy C-means Methods," International Journal of Machine Learning, vol. 2, no. 1, pp. 7-12, 2012. https://doi.org/10.7763/IJMLC.2012.V2.81

Copyright & License

Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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General Information

  • E-ISSN: 2972-368X
  • Abbreviated Title: Int. J. Mach. Learn.
  • DOI: 10.18178/IJML
  • Frequency: Quarterly
  • Average Days to Accept: 68 days
  • Acceptance Rate: 27%
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • DOI: 10.18178/IJML
  • Abstracing/Indexing: Google Scholar, Crossref, ProQuest, Electronic Journals Library, CNKI.
  • E-mail: editor@ijml.org
  • APC: 500USD