The visualisation and subsequent quantification of the inner bone structure plays an important role for better
understanding the disease- or drug-induced changes of the bone in the context of osteoporosis.
Scaling indices (SIM) are well suited to quantify these structures on a local level, especially to discriminate between
plate-like and rod-like structural elements. Local filters based on wavelets (WVL) are a standard technique in texture
analysis. So far, they are mainly used for two-dimensional image data sets.
Here we extend the formalism of the spherical Mexican hat wavelets to the analysis of three-dimensional tomographic
images and evaluate its performance in comparison with scaling indices, histomorphometric measures and BMD.
&mgr;CT images with isotropic resolution of 30 x 30 x 30 &mgr;m of a sample of 19 trabecular bone specimen of human thoracic
vertebrae were acquired. In addition, the bone mineral density was measured by QCT. The maximum compressive
strength (MCS) was determined in a biomechanical test.
Some wavelet-based as well as all scaling index- based texture measures show a significantly higher correlation with
MCS (WVL: &rgr;2=0.54, SIM: &rgr;2=0.53-0.56) than BMD (&rgr;2=0.46), where we find slightly better correlations for SIM than
for WVL. The SIM and WVL results are comparable but not better to those obtained with histomorphometric measures
(BV/TV: &rgr;2=0.45, Tr. N.: &rgr;2=0.67, Tr.Sp.: &rgr;2=0.67).
In conclusion, WVL and SIM techniques can successfully be applied to &mgr;CT image data. Since the two measures
characterize the image structures on a local scale, they offer the possibility to directly identify and discriminate rods and
sheets of the trabecular structure. This property may give new insights about the bone constituents responsible for the