Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, 1111 Highland Avenue, Madison, WI, 53705, USA.
Department of Radiology, University of Wisconsin School of Medicine and Public Health, 600 Highland Avenue, Madison, WI, 53792, USA.
Med Phys. 2019 Jul;46(7):3013-3024. doi: 10.1002/mp.13549. Epub 2019 May 21.
In previous works, it has been demonstrated that for filtered backprojection (FBP) reconstruction-based computed tomography (CT) images, the measured CT numbers are biased and the bias level decreases with increasing radiation dose. Low-dose scans typically include noise reduction schemes to reduce noise level. The purpose of this work was to investigate the potential impact of different noise reduction schemes on the CT number bias.
Three different filtration methods: Gaussian, adaptive trimmed mean (ATM), and anisotropic diffusion (AD) were implemented to reduce noise. All filters were independently applied in three different domains: raw counts, log-processed sinogram, or reconstructed image domain. A quality assurance phantom was scanned on a benchtop CT cone beam CT system, at dose levels ranging from 0.6 to 4.0 mGy. The conventional FBP reconstructions were performed to reconstruct CT images for the study of CT number biases. The CT number bias of different material inserts in the phantom was then measured. To further study the overall impact of CT number bias together with the potential consequences of noise reduction schemes on both the spatial resolution and noise characteristics, the task-based detectability of a high-contrast and high spatial resolution imaging task was used as an example to assess the performance of each noise reduction scheme. To qualitatively assess the impact of these noise reduction schemes on image, an anthropomorphic head phantom was also scanned on the benchtop CT system and processed with the above noise reduction schemes to generate images for demonstration.
Our results demonstrated the following major findings: (a) CT number bias can be significantly reduced when the noise reduction schemes are implemented in the raw counts domain; CT number bias cannot be reduced when these noise reduction schemes are implemented either in the reconstructed image domain or in the log-processed sinogram domain. (b) The extent of CT number bias reduction is dependent on both the material composition and noise reduction parameters. (c) The overall impact of the noise reduction schemes can be studied using the task-based detectability analysis framework and this framework can be used to select the appropriate parameters in each noise reduction scheme to optimize the performance for a given imaging task.
Noise reduction schemes can be used to considerably reduce CT number bias when they are implemented in the raw counts domain; however, their application cannot be arbitrarily extended to either the log-processed sinogram data domain or image domain. Trade-offs between bias reduction and overall image quality must be studied for an optimal performance of a given imaging task.
在以前的工作中，已经证明对于滤波反投影（FBP）重建的计算机断层扫描（CT）图像，测量的 CT 值存在偏差，并且随着辐射剂量的增加，偏差水平降低。低剂量扫描通常包括噪声降低方案以降低噪声水平。本工作的目的是研究不同噪声降低方案对 CT 值偏差的潜在影响。
实施了三种不同的滤波方法：高斯滤波、自适应修剪均值（ATM）滤波和各向异性扩散（AD）滤波，以降低噪声。所有滤波器都分别在三个不同的域中独立应用：原始计数、对数处理的正弦图或重建图像域。在台式 CT 锥形束 CT 系统上对质量保证体模进行扫描，剂量水平范围为 0.6 至 4.0 mGy。进行常规 FBP 重建以研究 CT 值偏差的 CT 图像。然后测量体模中不同材料插入物的 CT 值偏差。为了进一步研究 CT 值偏差的整体影响以及噪声降低方案对空间分辨率和噪声特性的潜在影响，使用高对比度和高空间分辨率成像任务的基于任务的可探测性作为示例来评估每个噪声降低方案的性能。为了定性评估这些噪声降低方案对图像的影响，还在台式 CT 系统上对人体头部模型进行了扫描，并使用上述噪声降低方案生成图像进行演示。
我们的结果表明了以下主要发现：（a）当噪声降低方案在原始计数域中实施时，CT 值偏差可以显著降低；当这些噪声降低方案在重建图像域或对数处理的正弦图域中实施时，CT 值偏差不能降低。（b）CT 值偏差降低的程度取决于材料组成和噪声降低参数。（c）可以使用基于任务的可探测性分析框架研究噪声降低方案的整体影响，并且可以使用该框架在每个噪声降低方案中选择适当的参数，以优化给定成像任务的性能。
当在原始计数域中实施时，噪声降低方案可以显著降低 CT 值偏差；然而，它们的应用不能任意扩展到对数处理的正弦图数据域或图像域。必须研究偏差降低和整体图像质量之间的权衡，以实现给定成像任务的最佳性能。
