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Digital mammograms analysis using fractal and multifractal methods

This paper presents a fractal and multifractal analysis for detection and segmentation of breast abnormalities using box counting method. The first step is the detection of the pathological breast by comparing parameters extracted from the multifractal spectrum of pairs of mammograms. The second consists to find the suspect region by decomposing the pathological mammogram into four blocks. The suspect region is characterized by a low value of Holder exponent, large values of asymmetry, lacunarity and fractal dimension. Finally, segmentation of some abnormalities is made on α-image and compared with k-means method. The whole process was applied on images of the Mini-Mias database. The obtained results are promising.