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在无法获取原始探测器计数的情况下校正统计CT数值偏差:在高空间分辨率光子计数CT成像中的应用

Correcting statistical CT number biases without access to raw detector counts: Applications to high spatial resolution photon counting CT imaging.

作者信息

Griner Dalton, Lei Nikou, Chen Guang-Hong, Li Ke

机构信息

Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.

Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.

出版信息

Med Phys. 2023 Oct;50(10):6022-6035. doi: 10.1002/mp.16657. Epub 2023 Jul 30.

Abstract

BACKGROUND

Due to the nonlinear nature of the logarithmic operation and the stochastic nature of photon counts (N), sinogram data of photon counting detector CT (PCD-CT) are intrinsically biased, which leads to statistical CT number biases. When raw counts are available, nearly unbiased statistical estimators for projection data were developed recently to address the CT number bias issue. However, for most clinical PCD-CT systems, users' access to raw detector counts is limited. Therefore, it remains a challenge for end users to address the CT number bias issue in clinical applications.

PURPOSE

To develop methods to correct statistical biases in PCD-CT without requiring access to raw PCD counts.

METHODS

(1) The sample variance of air-only post-log sinograms was used to estimate air-only detector counts, . (2) If the post-log sinogram data, y, is available, then N of each detector pixel was estimated using . Once N was estimated, a closed-form analytical bias correction was applied to the sinogram. (3) If a patient's post-log sinogram data are not archived, a forward projection of the bias-contaminated CT image was used to perform a first-order bias correction. Both the proposed sinogram domain- and image domain-based bias correction methods were validated using experimental PCD-CT data.

RESULTS

Experimental results demonstrated that both sinogram domain- and image domain-based bias correction methods enabled reduced-dose PCD-CT images to match the CT numbers of reference-standard images within [-5, 5] HU. In contrast, uncorrected reduced-dose PCD-CT images demonstrated biases ranging from -25 to 55 HU, depending on the material. No increase in image noise or spatial resolution degradation was observed using the proposed methods.

CONCLUSIONS

CT number bias issues can be effectively addressed using the proposed sinogram or image domain method in PCD-CT, allowing PCD-CT acquired at different radiation dose levels to have consistent CT numbers desired for quantitative imaging.

摘要

背景

由于对数运算的非线性性质以及光子计数(N)的随机性,光子计数探测器CT(PCD-CT)的正弦图数据存在固有偏差,这会导致统计CT值偏差。当有原始计数可用时,最近开发了用于投影数据的近似无偏统计估计器来解决CT值偏差问题。然而,对于大多数临床PCD-CT系统,用户对原始探测器计数的访问受到限制。因此,对于终端用户来说,在临床应用中解决CT值偏差问题仍然是一个挑战。

目的

开发无需访问原始PCD计数即可校正PCD-CT中统计偏差的方法。

方法

(1)仅空气的对数后正弦图的样本方差用于估计仅空气的探测器计数, 。(2)如果有对数后正弦图数据y,则使用 估计每个探测器像素的N。一旦估计出N,就对正弦图应用封闭形式的解析偏差校正。(3)如果未存档患者的对数后正弦图数据,则使用偏差污染的CT图像的前向投影进行一阶偏差校正。所提出的基于正弦图域和基于图像域的偏差校正方法均使用实验性PCD-CT数据进行了验证。

结果

实验结果表明,基于正弦图域和基于图像域的偏差校正方法都能使低剂量PCD-CT图像在[-5,5]HU范围内与参考标准图像的CT值相匹配。相比之下,未校正的低剂量PCD-CT图像根据材料不同显示出-25至55HU的偏差。使用所提出的方法未观察到图像噪声增加或空间分辨率下降。

结论

使用所提出的PCD-CT正弦图或图像域方法可以有效解决CT值偏差问题,从而使在不同辐射剂量水平下采集的PCD-CT具有定量成像所需的一致CT值。

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