Enhancement of microcalcifications on mammograms using a fractal modeling approach
The objective of this research is to model the mammographic parenchymal, ductal patterns and enhance microcalcifications using a 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 affine transformations. In this paper, a methodology based on fractal image modeling is developed to analyze and extract various mammographic textures. We show that general mammographic parenchymal and ductal patterns can be well modeled by the proposed approach. Therefore, microcalcifications can be enhanced by taking the difference between the original mammogram and modeled mammogram. 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 effective way to enhance microcalcifications, and thereby facilitate the radiologists' diagnosis. It is also able to improve the detection and classification of microcalcifications in a computer system.