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Quantitative computed tomography (QCT) is a widely used tool for osteoporosisdiagnosis and monitoring. The assessment of cortical markers like cortical bonemineral density (BMD) and thickness is a demanding task, mainly because of thelimited spatial resolution of QCT. We propose a direct model based method toautomatically identify the surface through the center of the cortex of humanvertebra. We develop a statistical bone model and analyze its probabilitydistribution after the imaging process. Using an as-rigid-as-possibledeformation we find the cortical surface that maximizes the likelihood of ourmodel given the input volume. Using the European Spine Phantom (ESP) and a highresolution \mu CT scan of a cadaveric vertebra, we show that the proposedmethod is able to accurately identify the real center of cortex ex-vivo. Todemonstrate the in-vivo applicability of our method we use manually obtainedsurfaces for comparison.

An Analysis by Synthesis Approach for Automatic Vertebral Shape Identification in Clinical QCT