Towards the detection of microcalcifications on mammograms through Multifractal Detrended Fluctuation Analysis

In this paper, we propose a method based on a generalization of the multifractal detrended fluctuation analysis (MF-DFA) to the two-dimensionality, for the analysis of breast medical images, particularly grey scale images of mammograms. The existent generalization has been suitably applied in synthetic multifractal surfaces. However, when it is applied to natural images only some scaling laws are revealed, not reinforcing the relevance of the method in the field. Therefore, it is shown that the proposed method is appropriate for detecting signs of breast cancer in mammograms, such as microcalcifications, based on recent approaches of the self-similarity formalism. The accuracy of the method is analysed and discussed when applied to mammograms, revealing features distinguished by direct singularity information extraction.