A representation for mammographic image processing

An imaging process creates an image that contains information about certain characteristics of the objects in the scene. Inevitably, the information is confounded by changes in the imaging conditions and scene background and it becomes difficult to judge simply by looking at the image whether the objects have changed or whether the imaging conditions or background has changed. In mammography, one is interested in the former not the latter. In order to overcome this problem for image analysis it is necessary to normalise the image and/or the feature measurements. Here, the authors show how mammographic images can be normalised in the form of a representation that makes explicit quantitative measurements of the breast itself and the authors argue that this is the correct representation to use for mammographic image processing. In particular, the authors note that their representation can be generated from conventional and directly-digital mammograms since it represents the breast, not the imaging process. The paper starts with the reasoning behind, and a description of, the h_int representation which is a quantitative representation of the breast tissue. The next section demonstrates the power of the h_int representation: it allows one to simulate any projective X-ray examination and to simulate the appearance of anatomical structures within the breast. The authors follow this with a comparison between the h_int representation and a conventional representation from the point of view of invariance to imaging conditions and surrounding tissue