Preprocessing of screening mammograms based on local statistical models

Authors:
Jiří Grim
Affiliations:
Institute of Information Theory and Automation, Czech Republic
Venue:
Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies
Year:
2011

Citing 4
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Abstract

In a recent paper we have proposed evaluation of screening mammograms by means of local statistical model. The model describes local statistical properties of internal pixels of a small search window - as they occur when scanning the mammogram. It is defined as a mixture of Gaussian densities which can be estimated by EM algorithm from data obtained by shifting the search window. The estimated Gaussian mixture is used to compute at all window positions the log-likelihood values which can be displayed as grey levels at the respective window centers. The resulting log-likelihood image closely correlates with the structural details of the original mammogram and emphasizes potential malignant findings as untypical locations of high novelty. In this paper we discuss the possibilities to enhance the log-likelihood image for diagnostic purposes.