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.
|Number of pages||4|
|Publication status||Published - 2003|
|Event||Medical Image Understanding and Analysis '03 - Sheffield, United Kingdom|
Duration: 10 Jul 2003 → 11 Jul 2003
|Conference||Medical Image Understanding and Analysis '03|
|Period||10/07/03 → 11/07/03|