Sadowsky Ofri, Lee Junghoon, Sutter Edward Grant, Wall Simon J, Prince Jerry L, Taylor Russell H
Department of Computer Science, The Johns Hopkins University.
Proc SPIE Int Soc Opt Eng. 2009;7258:72585B-72585B12. doi: 10.1117/12.813405.
We demonstrate an improvement to cone-beam tomographic imaging by using a prior anatomical model. A protocol for scanning and reconstruction has been designed and implemented for a conventional mobile C-arm: a 9 inch image-intensifier OEC-9600. Due to the narrow field of view (FOV), the reconstructed image contains strong truncation artifacts. We propose to improve the reconstructed images by fusing the observed x-ray data with computed projections of a prior 3D anatomical model, derived from a subject-specific CT or from a statistical database (atlas), and co-registered (3D/2D) to the x-rays.The prior model contains a description of geometry and radiodensity as a tetrahedral mesh shape and density polynomials, respectively. A CT-based model can be created by segmentation, meshing and polynomial fitting of the object's CT study. The statistical atlas is created through principal component analysis (PCA) of a collection of mesh instances deformably-registered (3D/3D) to patient datasets.The 3D/2D registration method optimizes a pixel-based similarity score (mutual information) between the observed x-rays and the prior. The transformation involves translation, rotation and shape deformation based on the atlas. After registration, the image intensities of observed and prior projections are matched and adjusted, and the two information sources are blended as inputs to a reconstruction algorithm.We demonstrate recostruction results of three cadaveric specimens, and the effect of fusing prior data to compensate for truncation. Further uses of hybrid reconstruction, such as compensation for the scan's limited arc length, are suggested for future research.
我们展示了通过使用先验解剖模型对锥束断层成像的改进。已为传统的移动C形臂(9英寸图像增强器OEC - 9600)设计并实施了扫描和重建协议。由于视野(FOV)狭窄,重建图像包含强烈的截断伪影。我们建议通过将观察到的x射线数据与从特定受试者CT或统计数据库(图谱)导出并与x射线进行配准(3D/2D)的先验3D解剖模型的计算投影相融合来改善重建图像。先验模型分别包含作为四面体网格形状和密度多项式的几何形状和放射密度描述。基于CT的模型可以通过对物体的CT研究进行分割、网格化和多项式拟合来创建。统计图谱是通过对与患者数据集进行可变形配准(3D/3D)的一组网格实例进行主成分分析(PCA)创建的。3D/2D配准方法优化观察到的x射线与先验之间基于像素 的相似性得分(互信息)。该变换涉及基于图谱的平移、旋转和形状变形。配准后,观察到的投影和先验投影的图像强度进行匹配和调整,并且将这两个信息源作为重建算法的输入进行融合。我们展示了三个尸体标本的重建结果,以及融合先验数据以补偿截断的效果。建议未来研究进一步利用混合重建,例如补偿扫描的有限弧长。