Fractal Modeling of Mammogram and Enhancement of Microcalcifications

According to the theory of deterministic fractal geometry, images can be modeled by deterministic fractal objects which are attractors of sets of two dimensional affine transformations. In this paper, a fractal modeling approach is developed to analyze and model mammographic breast tissue background. We show that general mammographic parenchymal and ductal patterns can be well modeled by a set of parameters of affine transformations. Therefore, microcalcifications can be enhanced by taking the difference between the original image and the modeled image. Our results are compared with those of the partial wavelet reconstruction and morphological operation approaches. The evaluation results demonstrate that the fractal modeling method is an effective way to enhance microcalcifications, and thereby may facilitate the radiologists' diagnosis. It may also be able to improve the detection of microcalcifications in a computer system.