Expectation-maximization technique for fibro-glandular discs detection in mammography images

Authors:
Ali El-Zaart
Affiliations:
Department of Computer Science, College of Computer and Information Sciences, King Saud University, P.O. Box 51178, Riyadh 11543, Saudi Arabia
Venue:
Computers in Biology and Medicine
Year:
2010

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Abstract

Breast cancer is among the leading causes of death in women worldwide. Mammography is the most effective imaging method for detecting no-palpable early-stage breast cancer. Understanding the nature of data in mammography images is very important for developing a model that fits well the data. Statistical distributions are widely used on the modelling of the data. Gamma distribution is more suitable than Gaussian distribution for modelling the data in mammography images. In this paper, we will use Gamma distribution to model the data in mammography images. The histogram of images can be seen as a mixture of Gamma distributions. Thresholds are selected at the valleys of a multi-modal histogram. The estimation of thresholds is based on the statistical parameters of the histogram. The expectation-maximization technique with gamma distribution (EMTG) is therefore developed to estimate the statistical histogram parameters. The experimental results on mammography images using this technique showed improvement in the accuracy in detection of the fibro-glandular discs.