Ge Weiwei, Liu Zihao, Cui Hehe, Yuan Xiaogang, Yang Yidong
Department of Engineering and Applied Physics, University of Science and Technology of China, Hefei, Anhui 230026, People's Republic of China.
Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, People's Republic of China.
Phys Med Biol. 2024 Dec 27;70(1). doi: 10.1088/1361-6560/ad9db1.
A major limitation in cone beam CT (CBCT) application is the presence of metal artifacts when scanning metal-embedded objects or high attenuation materials. This study aims to develop a dual-energy based method for effective metal artifact reduction.The proposed method comprised three steps. Initially, the virtual monoenergetic (VM) projections were generated by combining high- and low-energy projections to mitigate metal artifacts caused by the beam hardening effect. Subsequently, the normalized metal artifact reduction (NMAR) projections were created using the VM projections through the NMAR method. Then, the NMAR CBCT was produced by reintegrating metal into the CBCT reconstructed from NMAR projections. Finally, the iterative reconstruction was employed to obtain the final CBCT, utilizing VM projections and the NMAR CBCT as the initial input. Validation of the proposed method was achieved through Monte Carlo (MC) simulations on digital dental and abdominal phantoms, and CBCT scanning on CIRS Model 062M head and body phantoms. The structural similarity index measurement (SSIM) and the root mean square error (RMSE) calculated within a metal-containing ROI were employed for image quality evaluation.Both the MC simulation and phantom scanning demonstrated that the proposed method was superior to the frequency split metal artifact reduction (FSMAR) method in mitigating artifacts and preserving anatomic details around metal. Averaged over four phantoms, the SSIM was enhanced from 99.48% with FSMAR to 99.86% with our proposed method, and the RMSE was reduced from 93.62 HU to 70.75 HU. Furthermore, the proposed method could be implemented with less than two minutes after GPU acceleration.The proposed dual-energy based metal artifact correction method effectively corrects metal artifacts and preserves tissue details surrounding the metal region by leveraging the strengths of VM, projection interpolation and iterative reconstruction techniques. It has strong potential of clinical implementation due to the superior performance in image quality and process efficiency.
锥形束CT（CBCT）应用中的一个主要限制是在扫描嵌入金属的物体或高衰减材料时会出现金属伪影。本研究旨在开发一种基于双能的有效减少金属伪影的方法。所提出的方法包括三个步骤。首先，通过组合高能和低能投影生成虚拟单能（VM）投影，以减轻由束硬化效应引起的金属伪影。随后，通过归一化金属伪影减少（NMAR）方法使用VM投影创建NMAR投影。然后，通过将金属重新整合到从NMAR投影重建的CBCT中来生成NMAR CBCT。最后，采用迭代重建以获得最终的CBCT，将VM投影和NMAR CBCT用作初始输入。通过对数字牙科和腹部体模进行蒙特卡罗（MC）模拟以及对CIRS 062M头部和身体体模进行CBCT扫描，对所提出的方法进行了验证。在含金属的感兴趣区域（ROI）内计算的结构相似性指数测量（SSIM）和均方根误差（RMSE）用于图像质量评估。MC模拟和体模扫描均表明，所提出的方法在减轻伪影和保留金属周围的解剖细节方面优于频率分割金属伪影减少（FSMAR）方法。在四个体模上进行平均，SSIM从FSMAR的99.48%提高到我们所提出方法的99.86%，RMSE从93.62 HU降低到70.75 HU。此外，在GPU加速后，所提出的方法可以在不到两分钟的时间内实现。所提出的基于双能的金属伪影校正方法通过利用VM、投影插值和迭代重建技术的优势，有效地校正了金属伪影并保留了金属区域周围的组织细节。由于在图像质量和处理效率方面的卓越性能，它具有很强的临床应用潜力。
