Oh Daejoong, Kim Sewon, Park Doohyun, Choi Seungwon, Song Hundong, Choi Yunsu, Moon Seunghyuk, Baek Jongduk, Hwang Dosik
School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea.
School of Integrated Technology, Yonsei Institute of Convergence Technology, Yonsei University, 85 Songdo-gwahak-ro, Yeonsu-gu, Incheon, 21983, South Korea.
Med Phys. 2018 Jun 29. doi: 10.1002/mp.13072.
Polychromatic x-rays are used in most computed tomography scanners. In this case, a beam-hardening effect occurs, which degrades the image quality and distorts the shapes of objects in the reconstructed images. When the beam-hardening artifact is not severe, conventional correction methods can reduce the artifact reasonably well. However, highly dense materials, such as iron and titanium, can produce more severe beam-hardening artifacts, which often cannot be corrected by conventional methods. Moreover, when the size of the metal is large, severe darks bands due to photon starvation as well as beam-hardening are generated. The purpose of our study was to develop a new method for correcting severe beam-hardening artifacts and severe dark bands using a high-order polynomial correction function and a prior-image-based linearization method.
The initial estimate of an image free of beam-hardening (a prior image) was constructed from the initial reconstruction of the original projection data. Its corresponding beam-hardening-free projection data (a prior projection) were calculated by a projection operator onto the prior image. A new beam-hardening correction function G(p ) with many high-order terms was effectively determined via a simple minimization process applied to the difference between the original projection data and the prior projection data. Using the determined correction function G(p ), a corrected linearized sinogram p can be obtained, which became effectively linear for the line integrals of the object. Final beam-hardening corrected images can be reconstructed from the linearized sinogram. The proposed method was evaluated in both simulation and real experimental studies.
All investigated cases in both simulations and real experiments showed that the proposed method effectively removed not only streaks for moderate beam-hardening artifacts but also dark bands for severe beam-hardening artifacts without causing structural and contrast distortion.
The prior-image-based linearization method exhibited better correction performance than conventional methods. Because the proposed method did not require time-consuming iterative reconstruction processes to obtain the optimal correction function, it can expedite the correction procedure and incorporate more high-order terms in the linearization correction function in comparison to the conventional methods.
大多数计算机断层扫描扫描仪使用多色X射线。在这种情况下，会出现束硬化效应，这会降低图像质量并使重建图像中物体的形状失真。当束硬化伪影不严重时，传统的校正方法可以较好地减少伪影。然而，铁和钛等高密度材料会产生更严重的束硬化伪影，传统方法通常无法校正这些伪影。此外，当金属尺寸较大时，会产生由于光子饥饿以及束硬化导致的严重暗带。我们研究的目的是开发一种新方法，使用高阶多项式校正函数和基于先验图像的线性化方法来校正严重的束硬化伪影和严重的暗带。
从原始投影数据的初始重建中构建无束硬化图像（先验图像）的初始估计。通过投影算子将其对应的无束硬化投影数据（先验投影）计算到先验图像上。通过对原始投影数据和先验投影数据之间的差异应用简单的最小化过程，有效地确定了具有许多高阶项的新束硬化校正函数G(p)。使用确定的校正函数G(p)，可以获得校正后的线性化正弦图p，它对于物体的线积分有效地变为线性。最终的束硬化校正图像可以从线性化正弦图中重建。所提出的方法在模拟和实际实验研究中均进行了评估。
模拟和实际实验中的所有研究案例均表明，所提出的方法不仅有效地消除了中度束硬化伪影的条纹，还消除了严重束硬化伪影的暗带，且不会导致结构和对比度失真。
基于先验图像的线性化方法表现出比传统方法更好的校正性能。由于所提出的方法不需要耗时的迭代重建过程来获得最佳校正函数，与传统方法相比，它可以加快校正过程并在线性化校正函数中纳入更多高阶项。
