Classification of Trabecular Bone Texture from RMI and CT Scan Images by Multi Resolution Analysis

Although bone mineral density measurements constitute one of the main clinical indicators of osteoporosis, we know that bone fragility risk is also related to deteriorations of osseous architecture. Medical imagery constitutes one means to appreciate in vivo bone screen, what is particularly important in tracking of the osteoporosis. This paper presents a method of bone textural RMI and CT scanner classification, based on the use of mulfifractal analysis by the WTMM-2d method, we propose the choice of three features to realize these images classification: the Holder exponents average at the peaks of Legendre spectrums, the wavelet transform skeleton density by pixel, and gradients directions variance. The preliminary results of 40 images directly resulting from two medical imaging (RMI and CT scan), prove to be interesting since 90% of cases are well estimated, and two classes instantaneous clustering of the results (one healthy patient class and one osteoporotic patient class) quite separate.