Bilateral filtering based sliding motion compensated 4D-CBCT: a simulation study

Objective This study reconstructed 4D-CBCT for fully automatic compensated sliding motion by incorporating the bilateral filtering into the Deformable Vector Field (DVF). Methods First, a motion compensated simultaneous algebraic reconstruction technique (Modified Simultaneous Algebra Reconstruction Technique, mSART) was used to generate a high quality reference phase by using all phase projection stogether with the initial 4D-DVFs, which were generated via Demons registration between 0% phase and each other phaseimage. The 4D-DVF was optimized by matching the forward projection of the deformed 0% phase with the measured projection of the target phase. The loss function’s DVF smoothing constrain term contained bilateral filtering kernel that contained: 1) an spatial domain Guassian kernel; 2) animage intensity domain Guassian kernel; and 3) a DVF domain Guassian kernel. By choosing suitable kernel variances, the sliding motion can be extracted. A non-linear conjugate gradient optimizer wasused. We validated the algorithm on a Non-Uniform Rotational B-spline based Cardiac-Torso (NCAT) phantom. Quantification was evaluated by: 1) the Root-Mean-Square-Error (RMSE) together with the Maximum-Error (MaxE); 2) the Dice coefficient of the extracted lung contour from the final reconstructed images and 3) the relative reconstruction error (RE) to evaluate the algorithm’s performance. Results The motion trajectory’s RMSE/MaxEare 0.796/1.02 mm for bilateral filtering reconstruction; and 2.704/4.08 mm for original reconstruction. Image content such a stherib position, the hearted gedefinition, the fibrous structures all had been better corrected with bilateral filtering. Conclusion We developed a bilateral filtering based fully automatic sliding motion compensated 4D-CBCT scheme. Digital phantom study confirmed the improved motion estimation and image reconstruction ability. It can be used as a 4D-CBCT image guidance tool for lung SBRT treatment. 摘要： 目的 将双边滤波引入基于可变形矢量场 (DVF) 的 4D-CBCT 重建, 实现全自动滑动运动补偿 4D-CBCT 重 建。 方法 首先利用所有相位投影, 用改良的运动补偿瞬时代数重建技术 (Modified Simultaneous Algebra Reconstruction Technique, mSART) 生成高质 量参考相位。初始 4D-DVF 通过 0% 相位和其他相位图像依次配准生成。之后通过 配准目标相位测量投影和参考相位变形到目标相位后的正投来优化求解 4D-DVF。优化过程中的损失函数平滑约束 项中引入双边滤波。其包含 3 个子核:空间域 Guassian 核; 图像强度域 Guassian 核; 和 DVF 域 Guassian 核。选择合适 的子核方差提取滑动运动, 采用非线性共轭梯度算子优化, 用 B 样条心脏躯干体模 (NURBS-based Cardiac-Torso phantom, NCAT phantom) 验证算法。采用量化评价指标: Root-Mean-Square-Error (RMSE) 和最大误差 (MaxE); 重建图 像提取的肺轮廓 Dice 系数和相对重建误差 (RE) 评价算法性能。 结果 NCAT 模体的双边滤波重建运动轨迹的 RMSE/MaxE 为 0.796/1.02 mm; 原始重建方法的相应结果为 2.704/4.08 mm。图像中的特定结构如肋骨位置, 心脏边缘 的定义, 纤维结构通过双边过滤都得到了更好的纠正。 结论 开发了一种基于双边滤波的全自动滑动运动补偿 4D-CBCT 方案, 数字模体研宄证实了改进的运动估计和图像重建能力, 其可被用作肺 SBRT 治疗的 4D-CBCT 图像引 导工具。