Multifractal analysis: Application to medical imaging

In this paper, we propose an approach for Medical image analysis to detect tumors and to distinguish between healthy and pathological tissue that are present in the brain and skin. Our analysis is based on wavelet and multifractal formalism. In this analysis, we calculated the best linear regression interval that gives good parameter values calculated from new multiresolution indicator, called the average wavelet coefficient, derived from the wavelet leaders. Two main contributions are brought up: first, we proposed a method for the estimation of multifractal features. Second, we revealed the potential of multifractal features to characterize tumor brain and skin melanoma. We analyzed, compared our estimator and simulated image against wavelet leaders.