By Topic

Microcalcification detection using a fuzzy inference system and support vector machines

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Kabbadj, Y. ; Fac. of Sci. of Rabat, Mohammed V Univ., Rabat, Morocco ; Regragui, F. ; Himmi, M.M.

Breast cancer remains one of the deadliest diseases among women. Microcalcifications can be an early indicator of a breast cancer. Thus when they are present their detection during a screening test is very crucial. But due to their small size and low contrast in mammographies their detection is difficult. Therefore many computer aided diagnosis mathods have been developped to help and assist rediologist during their screening tests. This paper presents a novel approach to detect microcalcifications on digitized mammaographies using fuzzy logic and support vector machines. Our method was tested on 16 mammograms from Mias database including both positive and negative cases. We have obtained very satisfactory results with a sensitivity of 99,60% and a specificity of 99,11% during the learning phase.

Published in:

Multimedia Computing and Systems (ICMCS), 2012 International Conference on

Date of Conference:

10-12 May 2012