College of Mathematics and Physics, Qingdao Science and Technology University, Qingdao, Shandong 266071, China.
School of Computer Science and Technology, Shandong University, Jinan, Shandong 250101, China.
J Healthc Eng. 2017;2017:1417270. doi: 10.1155/2017/1417270. Epub 2017 Sep 17.
Frame-based regularization method as one kind of sparsity representation method has been developed in recent years and has been proved to be an efficient method for CT image reconstruction. However, most of the developed CT image reconstruction methods are analysis-based frame methods. This paper proposes a novel frame-based balanced hybrid model with two sparse regularization terms for CT image reconstruction. We generalize the fast alternating direction method to solve the proposed model so that every subproblem can be easily solved. The numerical experiments suggest that the proposed hybrid balanced-based wavelet regularization scheme is efficient in terms of reducing the defined reconstruction root mean squared error and improving the signal to noise ratio in CT image reconstruction.
基于帧的正则化方法作为一种稀疏表示方法，近年来得到了发展，并已被证明是一种有效的 CT 图像重建方法。然而，大多数开发的 CT 图像重建方法都是基于分析的帧方法。本文提出了一种新的基于帧的平衡混合模型，具有两个稀疏正则化项，用于 CT 图像重建。我们将快速交替方向法推广到所提出的模型中，以便于求解每个子问题。数值实验表明，所提出的基于混合平衡的小波正则化方案在降低定义的重建均方根误差和提高 CT 图像重建中的信噪比方面是有效的。
