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Prostate implant reconstruction from C-arm images with motion-compensated tomosynthesis

机译:从具有运动补偿断层合成的C臂图像重建前列腺植入物

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摘要

>Purpose: Accurate localization of prostate implants from several C-arm images is necessary for ultrasound-fluoroscopy fusion and intraoperative dosimetry. The authors propose a computational motion compensation method for tomosynthesis-based reconstruction that enables 3D localization of prostate implants from C-arm images despite C-arm oscillation and sagging.>Methods: Five C-arm images are captured by rotating the C-arm around its primary axis, while measuring its rotation angle using a protractor or the C-arm joint encoder. The C-arm images are processed to obtain binary seed-only images from which a volume of interest is reconstructed. The motion compensation algorithm, iteratively, compensates for 2D translational motion of the C-arm by maximizing the number of voxels that project on a seed projection in all of the images. This obviates the need for C-arm full pose tracking traditionally implemented using radio-opaque fiducials or external trackers. The proposed reconstruction method is tested in simulations, in a phantom study and on ten patient data sets.>Results: In a phantom implanted with 136 dummy seeds, the seed detection rate was 100% with a localization error of 0.86 ± 0.44 mm (Mean ± STD) compared to CT. For patient data sets, a detection rate of 99.5% was achieved in approximately 1 min per patient. The reconstruction results for patient data sets were compared against an available matching-based reconstruction method and showed relative localization difference of 0.5 ± 0.4 mm.>Conclusions: The motion compensation method can successfully compensate for large C-arm motion without using radio-opaque fiducial or external trackers. Considering the efficacy of the algorithm, its successful reconstruction rate and low computational burden, the algorithm is feasible for clinical use.
机译:>目的:对于超声荧光透视融合术和术中剂量测定,必须从多个C臂图像中准确定位前列腺植入物。作者提出了一种基于断层合成的重建运动计算补偿方法,该方法可在C臂振荡和下垂的情况下从C臂图像进行前列腺植入物的3D定位。>方法:使用量角器或C型臂关节编码器测量C型臂的主轴旋转角度,同时测量其旋转角度。 C臂图像经过处理以获得仅包含种子的二进制图像,可从中重建感兴趣的体积。运动补偿算法通过最大化所有图像中投射在种子投影上的体素的数量来迭代地补偿C臂的2D平移运动。这消除了传统上使用不透射线基准点或外部跟踪器实现的C臂全姿势跟踪的需要。拟议的重建方法在模拟,体模研究和十个患者数据集中进行了测试。>结果:在植入了136个假种子的体模中,种子检测率为100%,定位误差为与CT相比0.86±0.44毫米(平均±STD)对于患者数据集,每名患者大约1分钟内可达到99.5%的检测率。将患者数据集的重建结果与可用的基于匹配的重建方法进行比较,结果表明相对定位差异为0.5±0.4 mm。>结论:运动补偿方法可以成功补偿大型C臂运动无需使用不透射线的基准或外部跟踪器。考虑到该算法的有效性,成功重建率和低计算量,该算法在临床上是可行的。

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