Fan-beam filtered-backprojection reconstruction without backprojection weight
Fan-beam filtered-backprojection reconstruction without backprojection weight
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DOI：
10.1088/0031-9155/52/11/019
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发表时间：
2007-06-07
影响因子：
3.5
通讯作者：
Lauritsch, Guenter
中科院分区：
文献类型：
--
作者：
Dennerlein, Frank;Noo, Frederic;Lauritsch, Guenter
在本文中，我们解决的问题，二维图像重建从扇形束数据采集沿着一个完整的2 π扫描。遵循滤波反投影（FBP）结构的传统方法需要加权反投影，其权重取决于要重建的点和源位置;此权重仅出现在发散光束几何形状的情况下。与从平行束数据重建相比，反投影权重意味着计算工作量的增加，并且还被认为对重建图像的噪声特性具有一些负面影响。我们在这里证明，直接从全扫描扇束数据的FBP重建是可能的，没有反投影的重量。使用计算机模拟的，现实的扇束数据，我们比较了我们的新的FBP公式，没有反投影的权重使用的FBP公式的基础上，所有数据的平等加权。在信噪比，空间分辨率和计算效率方面的比较。这些研究表明，我们建议的公式可以以几乎相同的空间分辨率产生噪声水平降低的图像。这种效果随着距离视场中心的距离而迅速增加，从中心处的0%到20 cm处的20%噪声减少，以及到25 cm处的40%噪声减少。此外，建议的方法是计算要求较低，并减少了计算时间与增益，被发现在12%和43%之间变化的计算机用于评估。
In this paper, we address the problem of two-dimensional image reconstruction from fan-beam data acquired along a full 2 pi scan. Conventional approaches that follow the filtered-backprojection (FBP) structure require a weighted backprojection with the weight depending on the point to be reconstructed and also on the source position; this weight appears only in the case of divergent beam geometries. Compared to reconstruction from parallel-beam data, the backprojection weight implies an increase in computational effort and is also thought to have some negative impacts on noise properties of the reconstructed images. We demonstrate here that direct FBP reconstruction from full-scan fan-beam data is possible with no backprojection weight. Using computer-simulated, realistic fan-beam data, we compared our novel FBP formula with no backprojection weight to the use of an FBP formula based on equal weighting of all data. Comparisons in terms of signal-to-noise ratio, spatial resolution and computational efficiency are presented. These studies show that the formula we suggest yields images with a reduced noise level, at almost identical spatial resolution. This effect increases quickly with the distance from the center of the field of view, from 0% at the center to 20% less noise at 20 cm, and to 40% less noise at 25 cm. Furthermore, the suggested method is computationally less demanding and reduces computation time with a gain that was found to vary between 12% and 43% on the computers used for evaluation.