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arXiv · 1812.00693

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

Stefan Reinhold. Timo Damm·Lukas Huber·Reimer Andresen·Reinhard Barkmann·Claus-C. Glüer·Reinhard Koch
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Abstract

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.

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Stefan Reinhold. Timo Damm, Lukas Huber, Reimer Andresen, Reinhard Barkmann, Claus-C. Glüer, Reinhard Koch. 2018-12-03. An Analysis by Synthesis Approach for Automatic Vertebral Shape Identification in Clinical QCT. https://doi.org/10.1007/978-3-030-12939-2_6

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