宽锥束螺旋CT重建算法

A. Zamyatin, K. Taguchi, M. Silver
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引用次数: 1

摘要

在实践中,锥形束CT重建通常使用近似feldkamp型算法,因为它们的灵活性和简单性;然而,当涉及到64排及更高的检测器行CT时,它们会产生锥束伪影,并且对于256排以上的检测器行CT图像质量变得不可接受。另一方面,精确的算法产生无伪影的图像,但计算要求更高,并且在控制噪声/分辨率权衡方面不是很灵活。我们提出了一种可以根据锥角轻松调整的锥光束算法。我们在64层真实数据和320层模拟数据上进行了测试。对于64层CT,它在图像质量和体积重建速度上都优于螺旋Feldkamp;采用相同的冗余加权减少了锥波束伪影,提高了噪声均匀性。因为加权是在卷积步骤之后完成的,我们可以使用n-PI Tam-Danielson窗口,一个精确的锥束加权。结果表明,对于图像质量,加权比滤波方向更重要。该方法具有良好的图像质量,不需要对切向滤波线进行重跳。在评估中,我们将所提出的算法与螺旋Feldkamp和1-PI和3-PI Katsevich算法进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reconstruction algorithm for wide cone beam helical CT
In practice cone beam CT reconstruction is often done using the approximate Feldkamp-type algorithms because of their flexibility and simplicity; however, when it comes to a 64- and higher detector row CT, they produce cone beam artifacts, and for 256+ detector-row CT image quality becomes unacceptable. The exact algorithms, on the other hand, produce artifact-free images but are much more computationally demanding and not very flexible in controlling noise/resolution trade-off. We propose a cone beam algorithm that can be easily adjusted depending on the cone angle. We tested it on 64-slice real data and 320-slice simulated data. For 64-slice CT it outperforms helical Feldkamp in both image quality and volume reconstruction speed; using the same redundancy weighting it reduces the cone beam artifact and improves noise uniformity. Because weighting is done after the convolution step, we can use the n-PI Tam-Danielson window, an exact cone beam weighting. We show that the weighting is more important than the filtering direction for image quality. The proposed method has good image quality without rebinning to tangential filtering lines. In evaluation we compare the proposed algorithm to helical Feldkamp and the 1-PI and 3-PI Katsevich algorithms.
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