Separating Background Texture and Image Structure in Mammograms

There have been several approaches to the classification of texture in images. Most approaches will take certain local attributes or features into account and base the classification on these measures. In here we demonstrate the use of a statistical approach to separate the structure and texture background present in images. Modelling is based on normal images which only contain a texture background. The resulting model is applied to images which contain abnormal image structures as well as a normal texture background. Especially for mammographic (and other medical application) this can provide useful information which can be used as a pre-processing tool to obtain the structures present in the image and at the same time get a robust classification of the background texture.