DART: A Practical Reconstruction Algorithm for Discrete Tomography
DART: A Practical Reconstruction Algorithm for Discrete Tomography
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DOI：
10.1109/tip.2011.2131661
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发表时间：
2011-09-01
影响因子：
10.6
通讯作者：
Sijbers, Jan
中科院分区：
文献类型：
--
作者：
Batenburg, Kees Joost;Sijbers, Jan
本文提出了一种离散层析成像的迭代重建算法，称为离散代数重建技术（DART）。如果已知扫描对象仅由几种不同的成分组成，则可以应用DART，每种成分对应于重建中的恒定灰度值。利用每个成分的灰度值的先验知识来将当前重建转向仅包含这些灰度值的重建。基于模拟CT数据和实验μ CT数据的实验，它表明，DART是能够计算更准确的重建从少量的投影图像，或从一个小的角度范围内，比替代方法。它还表明，DART可以有效地处理噪声投影数据，该算法是强大的相对于误差的灰度值的估计。
In this paper, we present an iterative reconstruction algorithm for discrete tomography, called discrete algebraic reconstruction technique (DART). DART can be applied if the scanned object is known to consist of only a few different compositions, each corresponding to a constant gray value in the reconstruction. Prior knowledge of the gray values for each of the compositions is exploited to steer the current reconstruction towards a reconstruction that contains only these gray values. Based on experiments with both simulated CT data and experimental mu CT data, it is shown that DART is capable of computing more accurate reconstructions from a small number of projection images, or from a small angular range, than alternative methods. It is also shown that DART can deal effectively with noisy projection data and that the algorithm is robust with respect to errors in the estimation of the gray values.