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Real‐time respiratory phase matching between 2D fluoroscopic images and 3D CT CT images for precise percutaneous lung biopsy

机译:2D荧光透视图像与3D CT CT图像之间的实时呼吸相位匹配精确经皮肺活检

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Purpose A 3D CT image is used along with real‐time 2D fluoroscopic images in the state‐of‐the‐art cone‐beam CT system to guide percutaneous lung biopsy ( PLB ). To improve the guiding accuracy by compensating for respiratory motion, we propose an algorithm for real‐time matching of 2D fluoroscopic images to multiple 3D CT images of different respiratory phases that is robust to the small movement and deformation due to cardiac motion. Methods Based on the transformations obtained from nonrigid registration between two 3D CT images acquired at expiratory and inspiratory phases, we first generate sequential 3D CT images (or a 4D CT image) and the corresponding 2D digitally reconstructed radiographs ( DRR s) of vessels. We then determine 3D CT images corresponding to each real‐time 2D fluoroscopic image, by matching the 2D fluoroscopic image to a 2D DRR . Results Quantitative evaluations performed with 20 clinical datasets show that registration errors of anatomical features between a 2D fluoroscopic image and its matched 2D DRR are less than 3?mm on average. Registration errors of a target lesion are determined to be roughly 3?mm on average for 10 datasets. Conclusions We propose a real‐time matching algorithm to compensate for respiratory motion between a 2D fluoroscopic image and 3D CT images of the lung, regardless of cardiac motion, based on a newly improved matching measure. The proposed algorithm can improve the accuracy of a guiding system for the PLB by providing 3D images precisely registered to 2D fluoroscopic images in real‐time, without time‐consuming respiratory‐gated or cardiac‐gated CT images.
机译:目的,3D CT图像在最先进的锥形束CT系统中使用实时2D透视图像以引导经皮肺活检(PLB)。为了通过补偿呼吸运动来提高引导精度,我们提出了一种算法,用于将2D透视图像的实时匹配算法与不同呼吸相的多个3D CT图像的算法,这对于心动引起的小运动和变形具有鲁棒。基于在呼气和吸气阶段获取的两个3D CT图像之间的非引导性登记获得的变换的方法,我们首先生成顺序3D CT图像(或4D CT图像)和容器的相应的2D数字重建射线照片(DRR)。然后,我们通过将2D透视图像与2D DRR匹配来确定对应于每个实时2D荧光透视图像的3D CT图像。结果使用20个临床数据集进行的定量评估表明,平均值2D荧光镜图像和其匹配的2D DRR之间的解剖学特征的登记误差小于3Ωmm。目标病变的注册误差是10个数据集的平均约为3?mm。结论我们提出了一种实时匹配算法,以补偿肺部2D荧光透视图像和3D CT图像之间的呼吸运动,无论心动如何,基于新改进的匹配度量。该算法可以通过在实时向2D透视图像精确地注册到2D透视图像的3D图像,改善PLB的引导系统的准确性,而不耗时呼吸门控或心脏门控CT图像。

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