Evaluation of interpolation methods for surface-based motion compensated tomographic reconstruction for cardiac angiographic C-arm data.
Evaluation of interpolation methods for surface-based motion compensated tomographic reconstruction for cardiac angiographic C-arm data.
复制标题
评估心脏血管造影 C 形臂数据基于表面的运动补偿断层扫描重建的插值方法。
DOI：
10.1118/1.4789593
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发表时间：
2013
期刊：
影响因子：
3.8
通讯作者：
Fahrig,Rebecca
中科院分区：
文献类型：
--
作者：
Müller,Kerstin;Schwemmer,Chris;Hornegger,Joachim;Zheng,Yefeng;Wang,Yang;Lauritsch,Günter;Rohkohl,Christopher;Maier,AndreasK;Schultz,Carl;Fahrig,Rebecca
目的：对于介入心脏手术，有关心腔的解剖和功能信息是主要的兴趣。使用血管造影C形臂系统技术，可以从2D旋转血管造影投影数据（C形臂CT）重建术中三维（3D）图像。然而，动态对象的3D重建是C形臂CT重建中的基本问题。在几秒钟的扫描时间内采集2D投影，因此投影数据显示心脏的不同状态。标准FDK重建算法将使用所有采集的数据进行滤波反投影，并产生运动模糊图像。在该方法中，使用需要3D心脏运动的知识的运动补偿重建算法。运动估计从先前提出的3D动态表面模型。该动态表面模型导致在控制点处定义的稀疏运动矢量场（MVF）。为了执行运动补偿重建，需要密集的运动矢量场。密集MVF是通过稀疏MVF的插值生成的。因此，不同的运动插值方法对重建图像quality.Methods的影响进行了评估：四种不同的插值方法，薄板样条（TPS），谢泼德的方法，平滑加权函数，和一个简单的平均，进行了评估。在体模数据、猪模型以及活体临床数据集上测量重建质量。作为一个质量指标，前向投影的运动补偿重建心室和分割的2D心室血池的2D重叠定量测量与Dice相似系数和提取的心室轮廓之间的平均偏差。对体模数据集，在3D图像空间评价了归一化均方根误差（nRMSE）和通用质量指数（UQI）。体模实验中的定量结果显示，TPS和谢泼德方法的nRMSE相当，为0.047 ± 0.004。平滑加权函数和线性方法的结果仅略差。所有四种插值方法的UQI值均为99%。在临床人体数据集上，TPS插值明显获得了最佳结果。TPS重建和标准FDK重建之间的平均轮廓偏差在三个人的情况下，提高了1.52，1.34，和1.55 mm.The骰子系数表现出较低的灵敏度相对于在ventricular boundary.Conclusions的变化：在这项工作中，不同的运动插值方法对左心室运动补偿断层重建的影响进行了研究。采用TPS方法实现了体模、猪和人体临床数据集的最佳定量重建结果。通常，使用表面模型的运动估计和对密集MVF的运动插值的框架提供了使用运动补偿技术的断层摄影重建的能力。
Purpose:For interventional cardiac procedures, anatomical and functional information about the cardiac chambers is of major interest. With the technology of angiographic C‐arm systems it is possible to reconstruct intraprocedural three‐dimensional (3D) images from 2D rotational angiographic projection data (C‐arm CT). However, 3D reconstruction of a dynamic object is a fundamental problem in C‐arm CT reconstruction. The 2D projections are acquired over a scan time of several seconds, thus the projection data show different states of the heart. A standard FDK reconstruction algorithm would use all acquired data for a filtered backprojection and result in a motion‐blurred image. In this approach, a motion compensated reconstruction algorithm requiring knowledge of the 3D heart motion is used. The motion is estimated from a previously presented 3D dynamic surface model. This dynamic surface model results in a sparse motion vector field (MVF) defined at control points. In order to perform a motion compensated reconstruction, a dense motion vector field is required. The dense MVF is generated by interpolation of the sparse MVF. Therefore, the influence of different motion interpolation methods on the reconstructed image quality is evaluated.Methods:Four different interpolation methods, thin‐plate splines (TPS), Shepard's method, a smoothed weighting function, and a simple averaging, were evaluated. The reconstruction quality was measured on phantom data, a porcine model as well as onin vivoclinical data sets. As a quality index, the 2D overlap of the forward projected motion compensated reconstructed ventricle and the segmented 2D ventricle blood pool was quantitatively measured with the Dice similarity coefficient and the mean deviation between extracted ventricle contours. For the phantom data set, the normalized root mean square error (nRMSE) and the universal quality index (UQI) were also evaluated in 3D image space.Results:The quantitative evaluation of all experiments showed that TPS interpolation provided the best results. The quantitative results in the phantom experiments showed comparable nRMSE of ≈0.047 ± 0.004 for the TPS and Shepard's method. Only slightly inferior results for the smoothed weighting function and the linear approach were achieved. The UQI resulted in a value of ≈ 99% for all four interpolation methods. On clinical human data sets, the best results were clearly obtained with the TPS interpolation. The mean contour deviation between the TPS reconstruction and the standard FDK reconstruction improved in the three human cases by 1.52, 1.34, and 1.55 mm. The Dice coefficient showed less sensitivity with respect to variations in the ventricle boundary.Conclusions:In this work, the influence of different motion interpolation methods on left ventricle motion compensated tomographic reconstructions was investigated. The best quantitative reconstruction results of a phantom, a porcine, and human clinical data sets were achieved with the TPS approach. In general, the framework of motion estimation using a surface model and motion interpolation to a dense MVF provides the ability for tomographic reconstruction using a motion compensation technique.