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Female breast cancer is the major cause of death in occidental countries. Efforts in computer vision have been made in order to help improving the diagnostic accuracy by radiologists. We propose a methodology to distinguish Mass and Non-Mass tissues on mammograms. It is based on the computation of geostatistical measures (Moran's Index and Geary's Coefficient) over a multiresolution image representation trough wavelet transform. The computed measures are classified through a Support Vector Machine (SVM). The methodology reaches 98.36% of Specificity, 98.13% of Sensitivity and a rate of 98.24% to discriminate Mass from Non-Mass elements, using the Geary's Coefficient application.