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A Factorization Approach for Cone-Beam Reconstruction on a Circular Short-Scan

机译:圆形短扫描的锥形束重构的分解方法

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摘要

In this paper, we introduce a new algorithm for 3-D image reconstruction from cone-beam (CB) projections acquired along a partial circular scan. Our algorithm is based on a novel, exact factorization of the initial 3-D reconstruction problem into a set of independent 2-D inversion problems, each of which corresponds to finding the object density on one, single plane. Any such 2-D inversion problem is solved numerically using a projected steepest descent iteration scheme. We present a numerical evaluation of our factorization algorithm using computer-simulated CB data, without and with noise, of the FORBILD head phantom and of a disk phantom. First, we study quantitatively the impact of the reconstruction parameters on the algorithm performance. Next, we present reconstruction results for visual assessment of the achievable image quality and provide, for comparison, results obtained with two other state-of-the-art reconstruction algorithms for the circular short-scan.
机译:在本文中,我们介绍了一种新的3D图像重建算法,该算法可从沿部分圆形扫描获取的锥束(CB)投影进行重建。我们的算法基于一种新颖的,精确的将初始3-D重构问题分解为一组独立的2-D反演问题的方法,每个问题都对应于在一个单一平面上找到物体密度。使用计划的最速下降迭代方案,可以从数值上解决任何此类二维反演问题。我们使用计算机模拟的CB数据(无噪声和有噪声)对FORBILD头部模型和磁盘模型进行了因子分解算法的数值评估。首先,我们定量研究重建参数对算法性能的影响。接下来,我们提出用于视觉评估可达到的图像质量的重建结果,并提供用于圆形短扫描的其他两种最先进的重建算法所获得的结果进行比较,以进行比较。

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