23 February 2012 Automatic measurement of vertebral body deformations in CT images based on a 3D parametric model
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Abstract
Accurate and objective evaluation of vertebral body deformations represents an important part of the clinical diagnostics and therapy of pathological conditions affecting the spine. Although modern clinical practice is oriented towards threedimensional (3D) imaging techniques, the established methods for the evaluation of vertebral body deformations are based on measurements in two-dimensional (2D) X-ray images. In this paper, we propose a method for automatic measurement of vertebral body deformations in computed tomography (CT) images that is based on efficient modeling of the vertebral body shape with a 3D parametric model. By fitting the 3D model to the vertebral body in the image, quantitative description of normal and pathological vertebral bodies is obtained from the value of 25 parameters of the model. The evaluation of vertebral body deformations is based on the distance of the observed vertebral body from the distribution of the parameter values of normal vertebral bodies in the parametric space. The distribution is obtained from 80 normal vertebral bodies in the training data set and verified with eight normal vertebral bodies in the control data set. The statistically meaningful distance of eight pathological vertebral bodies in the study data set from the distribution of normal vertebral bodies in the parametric space shows that the parameters can be used to successfully model vertebral body deformations in 3D. The proposed method may therefore be used to assess vertebral body deformations in 3D or provide clinically meaningful observations that are not available when using 2D methods that are established in clinical practice.
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Darko Štern, Darko Štern, Miran Bürmen, Miran Bürmen, Vesna Njagulj, Vesna Njagulj, Boštjan Likar, Boštjan Likar, Franjo Pernuš, Franjo Pernuš, Tomaž Vrtovec, Tomaž Vrtovec, } "Automatic measurement of vertebral body deformations in CT images based on a 3D parametric model", Proc. SPIE 8315, Medical Imaging 2012: Computer-Aided Diagnosis, 831510 (23 February 2012); doi: 10.1117/12.911107; https://doi.org/10.1117/12.911107
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