Cresson T, Chav R, Branchaud D, Humbert L, Godbout B, Aubert B, Skalli W, De Guise J A
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:1008-11. doi: 10.1109/IEMBS.2009.5333869.
3D reconstructions of the spine from a frontal and sagittal radiographs is extremely challenging. The overlying features of soft tissues and air cavities interfere with image processing. It is also difficult to obtain information that is accurate enough to reconstruct complete 3D models. To overcome these problems, the proposed method efficiently combines the partial information contained in two images from a patient with a statistical 3D spine model generated from a database of scoliotic patients. The algorithm operates through two simultaneous iterating processes. The first one generates a personalized vertebra model using a 2D/3D registration process with bone boundaries extracted from radiographs, while the other one infers the position and the shape of other vertebrae from the current estimation of the registration process using a statistical 3D model. Experimental evaluations have shown good performances of the proposed approach in terms of accuracy and robustness when compared to CT-scan.
从正位和矢状位X光片进行脊柱的三维重建极具挑战性。软组织和空气腔的重叠特征会干扰图像处理。此外，要获取足够准确的信息来重建完整的三维模型也很困难。为了克服这些问题，所提出的方法有效地将来自患者的两张图像中包含的部分信息与从脊柱侧弯患者数据库生成的统计三维脊柱模型相结合。该算法通过两个同时进行的迭代过程运行。第一个过程使用从X光片中提取的骨边界通过二维/三维配准过程生成个性化的椎体模型，而另一个过程则使用统计三维模型根据配准过程的当前估计推断其他椎体的位置和形状。实验评估表明，与CT扫描相比，所提出的方法在准确性和鲁棒性方面具有良好的性能。
