  Quantitative computed tomography (QCT) is a widely used tool for osteoporosis
diagnosis and monitoring. The assessment of cortical markers like cortical bone
mineral density (BMD) and thickness is a demanding task, mainly because of the
limited spatial resolution of QCT. We propose a direct model based method to
automatically identify the surface through the center of the cortex of human
vertebra. We develop a statistical bone model and analyze its probability
distribution after the imaging process. Using an as-rigid-as-possible
deformation we find the cortical surface that maximizes the likelihood of our
model given the input volume. Using the European Spine Phantom (ESP) and a high
resolution \mu CT scan of a cadaveric vertebra, we show that the proposed
method is able to accurately identify the real center of cortex ex-vivo. To
demonstrate the in-vivo applicability of our method we use manually obtained
surfaces for comparison.
