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首页> 外文期刊>Journal of inverse and ill-posed problems >A non-smooth and non-convex regularization method for limited-angle CT image reconstruction
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A non-smooth and non-convex regularization method for limited-angle CT image reconstruction

机译：用于有限角度CT图像重建的非平滑和非凸正规化方法

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摘要

Restricted by the practical applications and radiation exposure of computed tomography (CT), the obtained projection data is usually incomplete, which may lead to a limited-angle reconstruction problem. Whereas reconstructing an object from limited-angle projection views is a challenging and ill-posed inverse problem. Fortunately, the regularization methods offer an effective way to deal with that. Recently, several researchers are absorbed in l(1) regularization to address such problem, but it has some problems for suppressing the limited-angle slope artifacts around edges due to incomplete projection data. In this paper, in order to surmount the ill-posedness, a non-smooth and non-convex method that is based on l(0) and l(1) regularization is presented to better deal with the limited-angle problem. Firstly, the splitting technique is utilized to deal with the presented approach called LWPC-ST-IHT. Afterwards, some propositions and convergence analysis of the presented approach are established. Numerical implementations show that our approach is more capable of suppressing the slope artifacts compared with the classical and state of the art iterative reconstruction algorithms.
机译：由计算机断层扫描（CT）的实际应用和辐射曝光的限制，所获得的投影数据通常不完整，这可能导致有限的角度重建问题。然而，从有限角度的投影视图重建对象是一个具有挑战性和不良反对问题的挑战性。幸运的是，正规化方法提供了处理该方法的有效方法。最近，几个研究人员在L（1）正则化中被吸收以解决此类问题，但是由于投影数据不完整的投影数据，它对抑制边缘的有限角度斜率伪影具有一些问题。在本文中，为了超越不良姿势，呈现基于L（0）和L（1）正则化的非平滑和非凸法，以更好地处理有限角度问题。首先，利用分割技术来处理称为LWPC-ST-IHT的呈现方法。之后，建立了提出的方法的一些主张和收敛分析。数值实施方式表明，与现实迭代重建算法的经典和状态相比，我们的方法更能抑制斜坡伪像。

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