ENGINEERING & TECHNOLOGY IN INDIA

Strength for Today and Bright Hope for Tomorrow

ISSN 2472-8640

Volume 1:3 April 2016

Chief Editor
Dr. D. Nagarathinam, M.E., Ph.D.

Editors
         Dr. P. N. Rajnarayanan, M.E., Ph.D.
         Dr. K. Sudalaimani, M.E., Ph.D.
         Dr. S. Ramanathan, Ph.D. (Chemistry)
         David Bunce, M.S. (RIT, USA)

Language and Style Advisors
         G. Baskaran, Ph.D.
         Sam Mohanlal, Ph.D.

Executive Editor
         M. S. Thirumalai, Ph.D.

Back Issues of Engineering & Technology in India - From February 2016

HOME PAGE



BOOKS FOR YOU TO READ AND DOWNLOAD FREE!


BACK ISSUES


  • E-mail your articles and book-length reports to engineeringandtechnologyindia@gmail.com.
  • Your articles and book-length reports should be written following standard Stylesheets such as ASME reference and citation models.
  • The Editorial Board has the right to accept, reject, or suggest modifications to the articles submitted for publication, and to make suitable stylistic adjustments. High quality, academic integrity, ethics and morals are expected from the authors and discussants.
  • Would you like to announce the dates and venues of your conferences, seminars, etc., and also publish the outline proceedings of these programs? Send a report to Engineering & Technology in India, engineeringandtechnologyindia@gmail.com..

Copyright © 2015
M. S. Thirumalai

Publisher: M.S. Thirumalai
11249 Oregon Circle
Bloomington, MN 55438
USA




Mammographic Microcalcification Segmentation Using
Fuzzy C Means Clustering

Mekala.S., M.E.
Nishanthi.C., M.E. Student


Abstract

Breast cancer is one of the major causes of death among women. Mammography is the main test used for screening and early diagnosis. Early detection performed on X-ray mammography is the key to improve breast cancer prognosis. This paper presents a research on mammography images using Morphological operators and Fuzzy c means clustering for cancer tumor mass segmentation. The first step of the cancer signs detection should be a segmentation procedure able to distinguish masses and micro calcifications from background tissue using Morphological operators and finally fuzzy c- means clustering (FCM) algorithm has been implemented for intensity based segmentation. This method does not require any manual processing technique for classification, thus it can be assimilated for identifying benign and malignant areas in intelligent way. Moreover it gives good classification responses for compressed mammogram image. The goal of the proposed method is twofold: one is to preserve the details in Region of Interest (ROI) at low bit rate without affecting the diagnostic related information and second is to classify and segment the micro-calcification area in reconstructed mammogram image with high accuracy. The experimental result shows that the proposed model performance is good at achieving high sensitivity of 97.27%, specificity of 94.38%.

Keywords: Mammography, Micro calcification, Segmentation, Fuzzy c- means clustering.


This is only the beginning part of the article. PLEASE CLICK HERE TO READ THE ENTIRE ARTICLE IN PRINTER-FRIENDLY VERSION.


Mekala. S., M.E.
mekala.4138@gmail.com

Nishanthi. C., M.E. Student
nishachinnasamy93@gmail.com

Department of Electronics & Communication Engineering
Sri Subramanya College of Engineering & Technology
NH - 209, Sukkamanaickenpatti
Palani 624615
Tamil Nadu
India



CONTACT EDITOR