Zeng Gengsheng L, Li Ya, DiBella Edward V R
Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology, University of Utah, Salt Lake City, UT 84108, USA.
Department of Mathematics, Utah Valley University, Orem, UT 84058, USA.
Int J Imaging Syst Technol. 2013 Mar;23(1):53-58. doi: 10.1002/ima.22036.
This paper develops an FBP-MAP (Filtered Backprojection, Maximum ) algorithm to reconstruct MRI images from under-sampled data. An objective function is first set up for the MRI reconstruction problem with a data fidelity term and a Bayesian term. The Bayesian term is a constraint in the temporal dimension. This objective function is minimized using the calculus of variations. The proposed algorithm is non-iterative. Undersampled dynamic myocardial perfusion MRI data were used to test the feasibility of the proposed technique. It is shown that the non-iterative Fourier reconstruction method effectively incorporates the temporal constraint and significantly reduces the angular aliasing artifacts caused by undersampling. A significant advantage of the proposed non-iterative Fourier technique over the iterative techniques is its fast computation time.
本文开发了一种FBP-MAP（滤波反投影，最大值）算法，用于从不完整采样数据中重建MRI图像。首先针对MRI重建问题建立一个目标函数，该函数包含一个数据保真项和一个贝叶斯项。贝叶斯项是时间维度上的一个约束。使用变分法使该目标函数最小化。所提出的算法是非迭代的。利用欠采样的动态心肌灌注MRI数据来测试所提技术的可行性。结果表明，非迭代傅里叶重建方法有效地纳入了时间约束，并显著减少了由欠采样引起的角度混叠伪影。所提出的非迭代傅里叶技术相对于迭代技术的一个显著优点是其计算时间快。
