| 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 © 2015M. S. Thirumalai
 Publisher: M.S. Thirumalai11249 Oregon Circle
 Bloomington, MN 55438
 USA
 
 | 
 
 Mammographic Microcalcification Segmentation UsingFuzzy 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 
 
 |