CT(computed tomography)系统实际应用当中,经常会出现扫描数据不满足数据完备性条件的情况.针对不完全角度重建问题的研究,是目前迭代型算法研究中的一个热点.一系列基于带有约束的总变分最小化的重建算法近年来在不完全角度重建中取...CT(computed tomography)系统实际应用当中,经常会出现扫描数据不满足数据完备性条件的情况.针对不完全角度重建问题的研究,是目前迭代型算法研究中的一个热点.一系列基于带有约束的总变分最小化的重建算法近年来在不完全角度重建中取得了较好的效果,这其中基于交替方向法(alternating direction method,ADM)的重建算法表现出更好的性能.然而,ADM方法在求解过程中对矩阵求逆的处理效率不高,导致极大的计算开销.本文针对该问题,使用非精确ADM方法,利用线性近似的方式替换掉计算开销较大的项,使得矩阵求逆问题可以通过快速傅里叶变换加速实现.实验结果表明,本文提出的非精确交替方向总变分最小化重建算法与精确ADM重建算法相比,没有明显的精度损失,计算时间缩减30%左右.展开更多
Inspired by total variation(TV), this paper represents a new iterative algorithm based on diagonal total variation(DTV) to address the computed tomography image reconstruction problem. To improve the quality of a reco...Inspired by total variation(TV), this paper represents a new iterative algorithm based on diagonal total variation(DTV) to address the computed tomography image reconstruction problem. To improve the quality of a reconstructed image, we used DTV to sparsely represent images when iterative convergence of the reconstructed algorithm with TV-constraint had no effect during the reconstruction process. To investigate our proposed algorithm, the numerical and experimental studies were performed, and rootmean-square error(RMSE) and structure similarity(SSIM)were used to evaluate the reconstructed image quality. The results demonstrated that the proposed method could effectively reduce noise, suppress artifacts, and reconstruct highquality image from incomplete projection data.展开更多
文摘CT(computed tomography)系统实际应用当中,经常会出现扫描数据不满足数据完备性条件的情况.针对不完全角度重建问题的研究,是目前迭代型算法研究中的一个热点.一系列基于带有约束的总变分最小化的重建算法近年来在不完全角度重建中取得了较好的效果,这其中基于交替方向法(alternating direction method,ADM)的重建算法表现出更好的性能.然而,ADM方法在求解过程中对矩阵求逆的处理效率不高,导致极大的计算开销.本文针对该问题,使用非精确ADM方法,利用线性近似的方式替换掉计算开销较大的项,使得矩阵求逆问题可以通过快速傅里叶变换加速实现.实验结果表明,本文提出的非精确交替方向总变分最小化重建算法与精确ADM重建算法相比,没有明显的精度损失,计算时间缩减30%左右.
基金supported in part by the National Natural Science Foundation of China(No.61401049)the Chongqing Foundation and Frontier Research Project(Nos.cstc2016jcyjA0473,cstc2013jcyjA0763)+3 种基金the Graduate Scientific Research and Innovation Foundation of Chongqing,China(No.CYB16044)the Strategic Industry Key Generic Technology Innovation Project of Chongqing(No.cstc2015zdcy-ztzxX0002)China Scholarship Councilthe Fundamental Research Funds for the Central Universities Nos.CDJZR14125501,106112016CDJXY120003,10611CDJXZ238826
文摘Inspired by total variation(TV), this paper represents a new iterative algorithm based on diagonal total variation(DTV) to address the computed tomography image reconstruction problem. To improve the quality of a reconstructed image, we used DTV to sparsely represent images when iterative convergence of the reconstructed algorithm with TV-constraint had no effect during the reconstruction process. To investigate our proposed algorithm, the numerical and experimental studies were performed, and rootmean-square error(RMSE) and structure similarity(SSIM)were used to evaluate the reconstructed image quality. The results demonstrated that the proposed method could effectively reduce noise, suppress artifacts, and reconstruct highquality image from incomplete projection data.
