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 language | English |
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Pages | 137-140 |
Number of pages | 4 |
Publication status | Published - 10 Jul 2003 |
Externally published | Yes |
Event | Medical Image Understanding and Analysis 2003 - University of Sheffield, Sheffield, United Kingdom of Great Britain and Northern Ireland Duration: 10 Jul 2003 → 11 Jul 2003 |
Conference
Conference | Medical Image Understanding and Analysis 2003 |
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Abbreviated title | MIUA 2003 |
Country/Territory | United Kingdom of Great Britain and Northern Ireland |
City | Sheffield |
Period | 10 Jul 2003 → 11 Jul 2003 |