Yu Hengyong, Ye Yangbo, Wang Ge
CT Laboratory, Biomedical Imaging Division, VT-WFU School of Biomedical Engineering Virginia Tech, Blacksburg, VA 24061, USA.
J Xray Sci Technol. 2008 Jan 1;16(4):243-251.
The state-of-the-art technology for theoretically exact local computed tomography (CT) is to reconstruct an object function using the truncated Hilbert transform (THT) via the projection onto convex sets (POCS) method, which is iterative and computationally expensive. Here we propose to reconstruct the object function using the THT via singular value decomposition (SVD). First, we review the major steps of our algorithm. Then, we implement the proposed SVD method and perform numerical simulations. Our numerical results indicate that our approach runs two orders of magnitude faster than the iterative approach and produces an excellent region-of-interest (ROI) reconstruction that was previously impossible, demonstrating the feasibility of localized pre-clinical and clinical CT as a new direction for research on exact local image reconstruction. Finally, relevant issues are discussed.
理论上精确的局部计算机断层扫描（CT）的最先进技术是通过凸集投影（POCS）方法使用截断希尔伯特变换（THT）来重建目标函数，该方法是迭代的且计算成本高昂。在此，我们提出通过奇异值分解（SVD）使用THT来重建目标函数。首先，我们回顾算法的主要步骤。然后，我们实现所提出的SVD方法并进行数值模拟。我们的数值结果表明，我们的方法比迭代方法快两个数量级，并产生了以前无法实现的出色的感兴趣区域（ROI）重建，证明了局部临床前和临床CT作为精确局部图像重建研究新方向的可行性。最后，讨论了相关问题。
