Zheng Guoyan, Ballester Miguel A G, Styner Martin, Nolte Lutz-Peter
MEM Research Center, University of Bern, CH-3014, Bern, Switzerland.
Med Image Comput Comput Assist Interv. 2006;9(Pt 1):25-32. doi: 10.1007/11866565_4.
Reconstruction of patient-specific 3D bone surface from 2D calibrated fluoroscopic images and a point distribution model is discussed. We present a 2D/3D reconstruction scheme combining statistical extrapolation and regularized shape deformation with an iterative image-to-model correspondence establishing algorithm, and show its application to reconstruct the surface of proximal femur. The image-to-model correspondence is established using a non-rigid 2D point matching process, which iteratively uses a symmetric injective nearest-neighbor mapping operator and 2D thin-plate splines based deformation to find a fraction of best matched 2D point pairs between features detected from the fluoroscopic images and those extracted from the 3D model. The obtained 2D point pairs are then used to set up a set of 3D point pairs such that we turn a 2D/3D reconstruction problem to a 3D/3D one. We designed and conducted experiments on 11 cadaveric femurs to validate the present reconstruction scheme. An average mean reconstruction error of 1.2 mm was found when two fluoroscopic images were used for each bone. It decreased to 1.0 mm when three fluoroscopic images were used.
讨论了从二维校准荧光透视图像和点分布模型重建患者特异性三维骨表面的方法。我们提出了一种二维/三维重建方案，该方案将统计外推和正则化形状变形与迭代图像到模型对应建立算法相结合，并展示了其在重建股骨近端表面的应用。使用非刚性二维点匹配过程建立图像到模型的对应关系，该过程迭代地使用对称单射最近邻映射算子和基于二维薄板样条的变形，以找到从荧光透视图像中检测到的特征与从三维模型中提取的特征之间的最佳匹配二维点对的一部分。然后，使用获得的二维点对建立一组三维点对，从而将二维/三维重建问题转化为三维/三维问题。我们设计并在11具尸体股骨上进行了实验，以验证当前的重建方案。当每根骨头使用两张荧光透视图像时，平均重建误差为1.2毫米。当使用三张荧光透视图像时，误差降至1.0毫米。
