Real-time out-of-plane artifact subtraction tomosynthesis imaging using prior CT for scanning beam digital x-ray system.
Real-time out-of-plane artifact subtraction tomosynthesis imaging using prior CT for scanning beam digital x-ray system.
复制标题
使用现有 CT 进行扫描束数字 X 射线系统的实时平面外伪影减除断层合成成像。
DOI：
10.1118/1.4896818
复制
发表时间：
2014
期刊：
影响因子：
3.8
通讯作者：
Fahrig,Rebecca
中科院分区：
文献类型：
--
作者：
Wu,Meng;Fahrig,Rebecca
目的扫描束数字X射线系统（SBDX）是一种逆几何透视系统，具有高剂量效率，能够在多个平面上执行连续真实的实时断层合成。该系统可用于肺结节活检过程中的图像引导。然而，重建的图像遭受强烈的平面外伪影，由于小的断层角度system.MethodsThe作者提出了一个平面外伪影减影断层合成（OPAST）算法，利用事先CT体积，以增加运行时的图像处理。从项目到项目物理模型导出的模糊相加（BAA）分析模型允许生成断层合成图像，这些图像是移位相加（SAA）重建图像的良好近似。提出了一种计算实用算法，用于使用BAA模型模拟来自患者特定先前CT体积的图像和平面外伪影。描述了一种用于对准模拟图像和重建图像的3D图像配准算法。使用三个肺癌患者的CT数据评估BAA分析模型和OPAST算法的准确性。OPAST和图像配准算法也进行了测试，增加非刚性呼吸motions.ResultsImage相似性测量，包括相关系数，均方误差，和结构相似性指数，表明BAA模型是非常准确的模拟SAA图像从之前的CT SBDX系统。当SBDX图像和CT容积之间的位移在X方向上在±10 mm内时，BAA模型的位移变化效应可以忽略。通过从重建中减去模拟伪影，提高了结节的可见性和深度分辨率。图像配准和OPAST在存在增加的呼吸运动的情况下是鲁棒的。减影图像中的主要伪影是由真实的对象和先前的CT volume.ConclusionsTheir提出的先前CT增强OPAST重建算法提高了SBDX系统的肺结节可见性和深度分辨率之间的不匹配引起的。
PurposeThe scanning beam digital x‐ray system (SBDX) is an inverse geometry fluoroscopic system with high dose efficiency and the ability to perform continuous real‐time tomosynthesis in multiple planes. This system could be used for image guidance during lung nodule biopsy. However, the reconstructed images suffer from strong out‐of‐plane artifact due to the small tomographic angle of the system.MethodsThe authors propose an out‐of‐plane artifact subtraction tomosynthesis (OPAST) algorithm that utilizes a prior CT volume to augment the run‐time image processing. A blur‐and‐add (BAA) analytical model, derived from the project‐to‐backproject physical model, permits the generation of tomosynthesis images that are a good approximation to the shift‐and‐add (SAA) reconstructed image. A computationally practical algorithm is proposed to simulate images and out‐of‐plane artifacts from patient‐specific prior CT volumes using the BAA model. A 3D image registration algorithm to align the simulated and reconstructed images is described. The accuracy of the BAA analytical model and the OPAST algorithm was evaluated using three lung cancer patients’ CT data. The OPAST and image registration algorithms were also tested with added nonrigid respiratory motions.ResultsImage similarity measurements, including the correlation coefficient, mean squared error, and structural similarity index, indicated that the BAA model is very accurate in simulating the SAA images from the prior CT for the SBDX system. The shift‐variant effect of the BAA model can be ignored when the shifts between SBDX images and CT volumes are within ±10 mm in thexandydirections. The nodule visibility and depth resolution are improved by subtracting simulated artifacts from the reconstructions. The image registration and OPAST are robust in the presence of added respiratory motions. The dominant artifacts in the subtraction images are caused by the mismatches between the real object and the prior CT volume.ConclusionsTheir proposed prior CT‐augmented OPAST reconstruction algorithm improves lung nodule visibility and depth resolution for the SBDX system.