Zheng Guoyan, Nolte Lutz-Peter, Ferguson Stephen J
Institute for Surgical Technology and Biomechanics, University of Bern, Switzerland.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:4395-8. doi: 10.1109/IEMBS.2010.5627136.
Accurate three-dimensional (3D) models of lumbar vertebrae can enable image-based 3D kinematic analysis. The common approach to derive 3D models is by direct segmentation of CT or MRI datasets. However, these have the disadvantages that they are expensive, time-consuming and/or induce high-radiation doses to the patient. In this paper, we present a technique to reconstruct a scaled 3D lumbar vertebral model from a single two-dimensional (2D) lateral fluoroscopic image and a statistical shape model of the lumbar vertebrae. Four cadaveric lumbar spine segments (totally twelve lumbar vertebrae) were used to validate the technique. To evaluate the reconstruction accuracy, the surface models reconstructed from the lateral fluoroscopic images were compared to the associated ground truth data derived from a 3D CT-scan reconstruction technique. For each case, a surface-based matching was first used to recover the scale and the rigid transformation between the reconstructed surface models and the ground truth model before the distances between the two discrete surface models were computed. An average error of 1.0 mm was found when the present technique was used to reconstruct the surface models of all twelve lumbar vertebrae.
准确的腰椎三维（3D）模型能够实现基于图像的3D运动学分析。获取3D模型的常用方法是直接分割CT或MRI数据集。然而，这些方法存在缺点，即成本高、耗时且/或会给患者带来高辐射剂量。在本文中，我们提出了一种从单个二维（2D）侧位荧光透视图像和腰椎统计形状模型重建缩放3D腰椎模型的技术。使用了四个尸体腰椎节段（共十二个腰椎）来验证该技术。为了评估重建精度，将从侧位荧光透视图像重建的表面模型与从3D CT扫描重建技术获得的相关地面真值数据进行比较。对于每个病例，在计算两个离散表面模型之间的距离之前，首先使用基于表面的匹配来恢复重建表面模型与地面真值模型之间的比例和刚体变换。当使用本技术重建所有十二个腰椎的表面模型时，发现平均误差为1.0毫米。
