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Evaluation of interpolation methods for surface-based motion compensated tomographic reconstruction for cardiac angiographic C-arm data

机译：基于表面运动补偿层析成像重建心脏血管造影C臂数据的插值方法的评估

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>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 on in vivo clinical 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.
机译：>目的：对于介入性心脏手术，与心脏腔室有关的解剖学和功能信息非常重要。借助血管造影C臂系统技术，可以从2D旋转血管造影投影数据（C臂CT）重建过程内三维（3D）图像。但是，动态对象的3D重建是C臂CT重建的基本问题。在几秒钟的扫描时间内获取2D投影，因此投影数据显示了心脏的不同状态。标准的FDK重建算法会将所有采集的数据用于滤波后的反投影，并产生运动模糊的图像。在这种方法中，使用了需要了解3D心脏运动的运动补偿重建算法。该运动是根据先前介绍的3D动态表面模型估算的。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）。为了执行运动补偿的重建，需要密集的运动矢量场。通过对稀疏MVF进行插值来生成密集MVF。因此，评估了不同的运动插值方法对重构图像质量的影响。>方法：四种不同的插值方法，薄板样条（TPS），Shepard方法，平滑加权函数和简单平均，进行评估。在幻像数据，猪模型以及体内临床数据集上测量了重建质量。作为质量指标，使用Dice相似系数和提取的心室轮廓之间的平均偏差，定量测量前向投影运动补偿的重建心室和分段的2D心室血池的2D重叠。对于幻像数据集，还在3D图像空间中评估了归一化均方误差（nRMSE）和通用质量指数（UQI）。>结果：所有实验的定量评估表明，TPS插值提供了最好的结果。幻像实验中的定量结果表明，TPS和Shepard方法的nRMSE约为0.047±0.004。平滑加权函数和线性方法的结果仅差一点。对于所有四种插值方法，UQI得出的值约为99％。在临床人类数据集上，使用TPS插值显然可以得到最佳结果。在三例人类病例中，TPS重建与标准FDK重建之间的平均轮廓偏差提高了1.52、1.34和1.55 mm。 Dice系数对心室边界的变化显示出较小的敏感性。>结论：在这项工作中，研究了不同运动插值方法对左心室运动补偿层析成像重建的影响。使用TPS方法可获得幻像，猪和人类临床数据集的最佳定量重建结果。通常，使用表面模型进行运动估计的框架以及对密集MVF进行运动插值的框架提供了使用运动补偿技术进行断层图像重建的能力。

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