Structure reconstruction of 3D anatomy from bi-planar X-ray images is a challenging topic. Traditionally, the elastic-model-based method was used to reconstruct 3D shapes by deforming the control points on the elastic mesh. However, the reconstructed shape is not smooth because the limited control points are only distributed on the edge of the elastic mesh. Alternatively, statistical-model-based methods, which include shape-model-based and intensity-model-based methods, are introduced due to their smooth reconstruction. However, both suffer from limitations. With the shape-model-based method, only the boundary profile is considered, leading to the loss of valid intensity information. For the intensity-based-method, the computation speed is slow because it needs to calculate the intensity distribution in each iteration. To address these issues, we propose a new reconstruction method using X-ray images and a specimenʼ s CT data. Specifically, the CT data provides both the shape mesh and the intensity model of the vertebra. Intensity model is used to generate the deformation field from X-ray images, while the shape model is used to generate the patient specific model by applying the calculated deformation field. Experiments on the public synthetic dataset and clinical dataset show that the average reconstruction errors are 1.1 mm and 1.2 mm, separately. The average reconstruction time is 3 minutes.

中文翻译：

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通过两个X射线图像和一个CT模型重建腰椎的3D形状

从双平面X射线图像重建3D解剖结构是一个具有挑战性的话题。传统上，基于弹性模型的方法用于通过使弹性网格上的控制点变形来重建3D形状。但是，由于有限的控制点仅分布在弹性网格的边缘，因此重建的形状并不平滑。可替代地，由于其平滑的重构，引入了基于统计模型的方法，包括基于形状模型的方法和基于强度模型的方法。但是，两者都有局限性。使用基于形状模型的方法，仅考虑边界轮廓，从而导致有效强度信息的丢失。对于基于强度的方法，计算速度较慢，因为它需要在每次迭代中计算强度分布。为了解决这些问题，我们提出了一种使用X射线图像和标本的CT数据的新重建方法。具体而言，CT数据同时提供了椎骨的形状网格和强度模型。强度模型用于从X射线图像生成变形场，而形状模型用于通过应用计算出的变形场生成患者特定模型。在公共合成数据集和临床数据集上进行的实验表明，平均重建误差分别为1.1 mm和1.2 mm。平均重建时间为3分钟。而形状模型则通过应用计算出的变形场来生成患者特定模型。在公共合成数据集和临床数据集上进行的实验表明，平均重建误差分别为1.1 mm和1.2 mm。平均重建时间为3分钟。而形状模型则通过应用计算出的变形场来生成患者特定模型。在公共合成数据集和临床数据集上进行的实验表明，平均重建误差分别为1.1 mm和1.2 mm。平均重建时间为3分钟。