四维锥形束的CT重建:基于鲁棒主成分分析的运动补偿算法

Four-dimensional cone-beam CT reconstruction based on motion-compensated robust principal component analysis

目的为降低FDK图像中条形伪影对相位间运动变形场准确估计的影响,提出了基于鲁棒主成分分析(RPCA)的运动补偿重建算法。方法基于RPCA的运动补偿重建算法在传统的MC-FDK算法基础上针对运动变形场的估计进行改进,首先运用RPCA将锥形束CT图像分解为低秩和稀疏分量,再使用基于霍恩&舒克光流法对低秩图像进行不同相位图像间运动变形场估计,以此来降低原始图像中条形伪影对相位间运动变形场准确估计的影响。实验通过MATLAB软件编程对飞利浦16层螺旋CT获得的4D-CT图像以瓦里安EDGE加速器扫描几何进行反投影得到仿真体模数据,并使用Elekta Synergy系统的CBCT以半扇模式获得肺癌肿瘤患者的真实CB投影数据来验证算法性能。结果相比于传统的MC-FDK重建结果组织边界更加清晰,运动伪影减少;仿真数据重建结果显示本算法PSNR与SSIM较MC-FDK算法分别提高了25.4%与7.6%;与FDK算法相比分别提高了37.9%与17.6%。结论该方法可以实现相位间运动变形场的准确估计,改善锥形束CT图像重建质量。

Objective To propose a motion compensation reconstruction method based on robust principal component analysis(RPCA)to reduce the influence of streak artifacts on accurate estimation of interphase motion deformation fields.Methods We propose a RPCA motion compensation reconstruction algorithm to improve the estimation of motion deformation fields based on the traditional MC-FDK algorithm.RPCA was used to decompose the cone-beam computed tomography(CBCT)images into low-rank and sparse components,and the motion deformation fields between different phase images were then estimated using Horn and Schunck optical flow method from the low-rank images to reduce the influence of striping artifacts on the accuracy of estimation of interphase motion deformation fields.The performance of the algorithm was evaluated using simulation data and real data.The simulation phantom data was obtained by back-projection of 4D-CT images acquired from Philips 16-slice spiral CT using MATLAB software programming according to the scanning geometry of Varian Edge accelerator.The real patient data were obtained using the Elekta Synergy system of CBCT scanning system with half-fan mode CB projection data from lung cancer patients.Results Compared with images reconstructed using the traditional MC-FDK algorithm,the reconstructed image using the proposed method had clearer tissue boundaries with reduced motion artifact was reduced.The results of phantom data reconstruction showed that compared with the MC-FDK algorithm,the proposed algorithms resulted in improvements of PSNR by 25.4%and SSIM by 7.6%;compared with the FDK algorithm,PSNR was improved by 37.9%and SSIM by 17.6%.Conclusion The proposed algorithm can achieve accurate estimation of inter-phase motion deformation fields and improve the quality of the reconstructed CBCT images.