By Topic

Mammographic Images Enhancement and Denoising for Microcalbfication Detection Using Dyadic Wavelet Processing

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

4 Author(s)
Mencattini, A. ; Dept. of Electron. Eng., Rome Univ., Roma ; Salmeri, M. ; Lojacono, R. ; Caselli, F.

Mammography is the most effective method for early detection of breast diseases. However, the typical diagnostic signs, such as masses and microcalcifications, are difficult to be detected because mammograms are low contrast and noisy images. In this paper, we present an algorithm for mammographic images enhancement and denoising based on the wavelet transform. In particular, we develop an adaptive procedure to perform an optimal denoising using a local iterative fuzzy noise variance estimation. Moreover, the degree of enhancement is adoptively tuned at each scale. The proposed algorithm has been tested on clinical images

Published in:

Instrumentation and Measurement Technology Conference, 2006. IMTC 2006. Proceedings of the IEEE

Date of Conference:

24-27 April 2006