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CT 的经验束硬化校正(EBHC)。

Empirical beam hardening correction (EBHC) for CT.

机构信息

Institute of Medical Physics, University of Erlangen-Nürnberg, 91052 Erlangen, Germany.

出版信息

Med Phys. 2010 Oct;37(10):5179-87. doi: 10.1118/1.3477088.

Abstract

PURPOSE

Due to x-ray beam polychromaticity and scattered radiation, attenuation measurements tend to be underestimated. Cupping and beam hardening artifacts become apparent in the reconstructed CT images. If only one material such as water, for example, is present, these artifacts can be reduced by precorrecting the rawdata. Higher order beam hardening artifacts, as they result when a mixture of materials such as water and bone, or water and bone and iodine is present, require an iterative beam hardening correction where the image is segmented into different materials and those are forward projected to obtain new rawdata. Typically, the forward projection must correctly model the beam polychromaticity and account for all physical effects, including the energy dependence of the assumed materials in the patient, the detector response, and others. We propose a new algorithm that does not require any knowledge about spectra or attenuation coefficients and that does not need to be calibrated. The proposed method corrects beam hardening in single energy CT data.

METHODS

The only a priori knowledge entering EBHC is the segmentation of the object into different materials. Materials other than water are segmented from the original image, e.g., by using simple thresholding. Then, a (monochromatic) forward projection of these other materials is performed. The measured rawdata and the forward projected material-specific rawdata are monomially combined (e.g., multiplied or squared) and reconstructed to yield a set of correction volumes. These are then linearly combined and added to the original volume. The combination weights are determined to maximize the flatness of the new and corrected volume. EBHC is evaluated using data acquired with a modern cone-beam dual-source spiral CT scanner (Somatom Definition Flash, Siemens Healthcare, Forchheim, Germany), with a modern dual-source micro-CT scanner (Tomo-Scope Synergy Twin, CT Imaging GmbH, Erlangen, Germany), and with a modern C-arm CT scanner (Axiom Artis dTA, Siemens Healthcare, Forchheim, Germany). A large variety of phantom, small animal, and patient data were used to demonstrate the data and system independence of EBHC.

RESULTS

Although no physics apart from the initial segmentation procedure enter the correction process, beam hardening artifacts were significantly reduced by EBHC. The image quality for clinical CT, micro-CT, and C-arm CT was highly improved. Only in the case of C-arm CT, where high scatter levels and calibration errors occur, the relative improvement was smaller.

CONCLUSIONS

The empirical beam hardening correction is an interesting alternative to conventional iterative higher order beam hardening correction algorithms. It does not tend to over- or undercorrect the data. Apart from the segmentation step, EBHC does not require assumptions on the spectra or on the type of material involved. Potentially, it can therefore be applied to any CT image.

摘要

目的

由于 X 射线束的多色性和散射辐射,衰减测量往往被低估。在重建的 CT 图像中,会出现杯状和束硬化伪影。如果只有一种材料,例如水,这些伪影可以通过预先校正原始数据来减少。当存在多种材料(如水和骨,或水和骨和碘)时,更高阶的束硬化伪影需要迭代束硬化校正,其中图像被分割成不同的材料,并将这些材料正向投影以获得新的原始数据。通常,正向投影必须正确模拟束多色性并考虑所有物理效应,包括患者中假定材料的能量依赖性、探测器响应等。我们提出了一种新的算法,该算法不需要任何关于光谱或衰减系数的知识,也不需要校准。所提出的方法校正单能 CT 数据中的束硬化。

方法

EBHC 唯一的先验知识是将物体分割成不同的材料。除水以外的材料通过原始图像分割,例如通过简单的阈值处理。然后,对这些其他材料进行(单色)正向投影。将测量的原始数据和正向投影的特定材料原始数据以单项式组合(例如,相乘或平方)并重建,以生成一组校正体积。然后将这些体积线性组合并添加到原始体积中。组合权重的确定是为了最大化新校正体积的平坦度。使用现代锥形束双源螺旋 CT 扫描仪(Somatom Definition Flash,Siemens Healthcare,Forchheim,德国)、现代双源微 CT 扫描仪(Tomo-Scope Synergy Twin,CT Imaging GmbH,Erlangen,德国)和现代 C 臂 CT 扫描仪(Axiom Artis dTA,Siemens Healthcare,Forchheim,德国)采集的数据来评估 EBHC。使用各种体模、小动物和患者数据来证明 EBHC 的数据和系统独立性。

结果

尽管校正过程除了初始分割步骤之外没有任何物理知识,但 EBHC 显著减少了束硬化伪影。临床 CT、微 CT 和 C 臂 CT 的图像质量得到了很大的提高。只有在 C 臂 CT 的情况下,散射水平和校准误差较高,相对改善较小。

结论

经验性束硬化校正算法是传统迭代高阶束硬化校正算法的一种有趣替代方法。它不会过度或不足校正数据。除了分割步骤之外,EBHC 不需要对光谱或涉及的材料类型做出假设。因此,它有可能应用于任何 CT 图像。

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