Texture Segmentation in Mammograms

Reyer Zwiggelaar, Lilian Blot, David Raba, Erika R. E. Denton

Research output: Contribution to conferencePaperpeer-review

Abstract

We have investigated a combination of statistical modelling and expectation maximisation for a texture based approach to the segmentation of mammographic images. Texture modelling is based on the implicit incorporation of spatial information through the introduction of a set-permutation-occurrence matrix. Statistical modelling is used for dimensionality reduction, data generalisation and noise removal purposes. Expectation maximisation modelling of the resulting feature vector provides the basis for image segmentation. The developed segmentation results are used for automatic mammographic risk assessment
Original languageEnglish
Pages137-140
Number of pages4
Publication statusPublished - 10 Jul 2003
Externally publishedYes
EventMedical Image Understanding and Analysis 2003 - University of Sheffield, Sheffield, United Kingdom of Great Britain and Northern Ireland
Duration: 10 Jul 200311 Jul 2003

Conference

ConferenceMedical Image Understanding and Analysis 2003
Abbreviated titleMIUA 2003
Country/TerritoryUnited Kingdom of Great Britain and Northern Ireland
CitySheffield
Period10 Jul 200311 Jul 2003

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