We analyze mu-CT tomographic images of human trabecular bone in vitro.
We consider a sample consisting of 201 bone specimens harvested from six
different skeletal sites with bone fraction in the range BV/TV is an
element of [0.04, 0.075]. Using the local characterization of the bone
trabecular network given by isotropic and anisotropic scaling indices,
we apply classification algorithms in order to reveal structural
similarities in the sample. The classification procedures based on
isotropic and anisotropic scaling indices lead to different clustering
solutions. This comparison helps revealing interesting site specific
structural features connected to the intrinsic anisotropy of the
trabecular network.
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We analyze mu-CT tomographic images of human trabecular bone in vitro.
We consider a sample consisting of 201 bone specimens harvested from six
different skeletal sites with bone fraction in the range BV/TV is an
element of [0.04, 0.075]. Using the local characterization of the bone
trabecular network given by isotropic and anisotropic scaling indices,
we apply classification algorithms in order to reveal structural
similarities in the sample. The classification procedures based on
isotropic and...
»