COMPUTING THE SCATTER COMPONENT OF MAMMOGRAPHIC IMAGES

This paper builds upon a technical report in which we proposed a model of the mammographic imaging process for which scattered radiation is a kev degrading factor. In this paper, we propose a way of estimating the scatter component of the signal at any pixel within a mammographic image, and we use this estimate for model-based image enhancement. The first step is to extend our previous model to divide breast tissue into ''interesting'' (fibrous/glandular/cancerous) tissue and fat. The scatter model is then based on the idea that the amount of scattered radiation reaching a point is related to the energy imparted to the surrounding neighbourhood. This complex relationship is approximated using published empirical data, and it varies with the size of the breast being imaged. The approximation is further complicated by needing to take account of extra-focal radiation and breast edge effects. The approximation takes the form of a weighting mask which is convolved with the total signal (primary and scatter) to give a value which is input to a ''scatter function'', approximated using three reference cases, and which returns a scatter estimate. Given a scatter estimate, the more important primary component can be calculated and used to create an image recognizable by a radiologist. The images resulting from this process are clearly enhanced, and model verification tests based on an estimate of the thickness of interesting tissue present proved to be very successful. A good scatter model opens the way for further processing to remove the effects of other degrading factors, such as beam hardening.