Fractal Modeling and Segmentation forthe Enhancement of Microcalci cations inDigital Mammograms

The objective of this research is to model the mammographic parenchymal, ductal patterns and enhance the microcalciications using deterministic fractal approach. According to the theory of deterministic fractal geometry, images can be modeled by deterministic fractal objects which are attractors of sets of two dimensional aane transformations. The Iterated Functions Systems and the Collage Theorem are the mathematical foundations of fractal image modeling. In this paper, a methodology based on fractal image modeling is developed to analyze and model breast background structures. We show that general mammographic parenchymal and ductal patterns can be well modeled by a set of parameters of aane transformations. Therefore, microcalciications can be enhanced by taking the diierence between the original image and the modeled image. Our results are compared with those of the partial wavelet reconstruction and morphological operation approaches. The results demonstrate that the fractal modeling method is an eeective way to enhance microcalciica-tions. It may also be able to improve the detection and classiication of microcalciications in a computer-aided diagnosis system.