南方医科大学学报 ›› 2016, Vol. 36 ›› Issue (07): 969-.

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基于运动补偿的压缩感知4D-CBCT优质重建

杨轩,张华,何基,曾栋,张忻宇,边兆英,张敬,马建华   

  • 出版日期:2016-07-20 发布日期:2016-07-20

Motion-compensated compressed sensing four-dimensional cone-beam CT reconstruction

  • Online:2016-07-20 Published:2016-07-20

摘要: 受硬件限制,4D-CBCT成像中单个呼吸相位对应投影数目过少,而相应的常规解析算法重建图像中充斥着大量噪声和伪 影。为解决此问题,鉴于当前呼吸相位图像可以通过其它呼吸相位图像运动补偿获取,本文中我们提出一种利用多相位投影数 据重建4D-CBCT的策略。本文中我们构建了包含基于多相位投影数据的保真项和基于压缩感知理论的全变分正则化的代价 函数。对于投影数据保真项的设计,不再局限于当前相位投影数据,而是利用多个相位投影数据通过变形的成像模型联合构 建。对于复杂代价函数的优化,我们利用GPBL(Gradient-Projection-Barzilai-Linesearch, GPBL)算法来实现。物理体模及临床 数据实验结果表明,相对于解析算法及代数迭代全变分约束算法,新方法在噪声和伪影的抑制方面有上佳表现,引入不同相位 图像间的关联信息并未引入新的伪影和运动模糊。

Abstract: Restriction by hardware caused the very low projection number at a single phase for 4-dimensional cone beam (4D-CBCT) CT imaging, and reconstruction using conventional reconstruction algorithms is thus constrained by serious streak artifacts and noises. To address this problem, we propose an approach to reconstructing 4D-CBCT images with multi-phase projections based on the assumption that the image at one phase can be viewed as the motion-compensated image at another phase. Specifically, we formulated a cost function using multi-phase projections to construct the fidelity term and the TV regularization method. For fidelity term construction, the projection data of the current phase and those at other phases were jointly used by reformulating the imaging model. The Gradient-Projection-Barzilai-Line search (GPBL) method was used to optimize the complex cost function. Physical phantom and patient data results showed that the proposed approach could effectively reduce the noise and artifacts, and the introduction of additional temporal correlation did not introduce new artifacts or motion blur.