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A hybrid reconstruction algorithm for fast and accurate 4D cone-beam CT imaging

机译:快速准确的4D锥形束CT成像的混合重建算法

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Purpose: 4D cone beam CT (4D-CBCT) has been utilized in radiation therapy to provide 4D image guidance in lung and upper abdomen area. However, clinical application of 4D-CBCT is currently limited due to the long scan time and low image quality. The purpose of this paper is to develop a new 4D-CBCT reconstruction method that restores volumetric images based on the 1-min scan data acquired with a standard 3D-CBCT protocol.Methods: The model optimizes a deformation vector field that deforms a patient-specific planning CT (p-CT), so that the calculated 4D-CBCT projections match measurements. A forward-backward splitting (FBS) method is invented to solve the optimization problem. It splits the original problem into two well-studied subproblems, i.e., image reconstruction and deformable image registration. By iteratively solving the two subproblems, FBS gradually yields correct deformation information, while maintaining high image quality. The whole workflow is implemented on a graphic-processing-unit to improve efficiency. Comprehensive evaluations have been conducted on a moving phantom and three real patient cases regarding the accuracy and quality of the reconstructed images, as well as the algorithm robustness and efficiency.Results: The proposed algorithm reconstructs 4D-CBCT images from highly under-sampled projection data acquired with 1-min scans. Regarding the anatomical structure location accuracy, 0.204 mm average differences and 0.484 mm maximum difference are found for the phantom case, and the maximum differences of 0.3-0.5 mm for patients 1-3 are observed. As for the image quality, intensity errors below 5 and 20 HU compared to the planning CT are achieved for the phantom and the patient cases, respectively. Signal-noise-ratio values are improved by 12.74 and 5.12 times compared to results from FDK algorithm using the 1-min data and 4-min data, respectively. The computation time of the algorithm on a NVIDIA GTX590 card is 1-1.5 min per phase.Conclusions: High-quality 4D-CBCT imaging based on the clinically standard 1-min 3D CBCT scanning protocol is feasible via the proposed hybrid reconstruction algorithm.
机译:目的:4D锥形束CT(4D-CBCT)已用于放射治疗,以在肺和上腹部区域提供4D图像引导。但是,由于扫描时间长和图像质量低,目前4D-CBCT的临床应用受到限制。本文的目的是开发一种新的4D-CBCT重建方法,该方法可基于使用标准3D-CBCT协议获取的1分钟扫描数据恢复体积图像。方法:该模型优化了使患者变形的变形矢量场-具体的计划CT(p-CT),以便计算出的4D-CBCT投影与测量值匹配。发明了一种前向后拆分(FBS)方法来解决优化问题。它将原始问题分为两个经过充分研究的子问题,即图像重建和可变形图像配准。通过迭代解决两个子问题,FBS逐渐产生正确的变形信息,同时保持较高的图像质量。整个工作流程在图形处理单元上实施,以提高效率。对运动体模和三个真实患者案例进行了全面评估,评估了重建图像的准确性和质量以及算法的鲁棒性和效率。结果:所提出的算法从高度欠采样的投影数据中重建4D-CBCT图像通过1分钟扫描获得。关于解剖结构的位置精度,幻影病例的平均差异为0.204mm,最大差异为0.484mm,1-3例患者的最大差异为0.3-0.5mm。至于图像质量,与计划的CT相比,幻影和患者情况的强度误差分别低于5 HU和20 HU。与使用1分钟数据和4分钟数据的FDK算法的结果相比,信噪比值分别提高了12.74和5.12倍。该算法在NVIDIA GTX590卡上的计算时间为每相1-1.5分钟。结论:通过提出的混合重建算法,基于临床标准1分钟3D CBCT扫描协议的高质量4D-CBCT成像是可行的。

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