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基于运动补偿断层合成的 C 臂图像的前列腺植入物重建。

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

机构信息

School of Computing, Queen's University, Kingston, Ontario, Canada.

出版信息

Med Phys. 2011 Oct;38(10):5290-302. doi: 10.1118/1.3633897.

Abstract

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.

摘要

目的

从多个 C 臂图像准确定位前列腺植入物对于超声-荧光透视融合和术中剂量学非常重要。作者提出了一种基于断层合成的计算运动补偿方法,即使在 C 臂摆动和下垂的情况下,也可以从 C 臂图像中对前列腺植入物进行 3D 定位。

方法

通过围绕其主轴线旋转 C 臂,同时使用量角器或 C 臂关节编码器测量其旋转角度,来捕获 5 个 C 臂图像。对 C 臂图像进行处理,从其中获取仅种子的二进制图像,然后从该图像重建感兴趣的体积。运动补偿算法通过最大化在所有图像中投影到种子投影的体素数量,迭代地补偿 C 臂的 2D 平移运动。这避免了传统上使用放射性不透射线标记物或外部跟踪器实现的 C 臂全姿态跟踪的需要。在所提出的重建方法中,在模拟、体模研究和十个患者数据集上进行了测试。

结果

在植入 136 个假种子的体模中,与 CT 相比,种子检测率为 100%,定位误差为 0.86±0.44mm(平均值±标准差)。对于患者数据集,大约在每个患者 1 分钟内实现了 99.5%的检测率。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了比较,显示相对定位差异为 0.5±0.4mm。

结论

该运动补偿方法可以在不使用放射性不透射线标记物或外部跟踪器的情况下成功补偿大的 C 臂运动。考虑到算法的功效、成功的重建率和低的计算负担,该算法适用于临床应用。

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