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本文引用的文献

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Cone-Beam CT with a Flat-Panel Detector: From Image Science to Image-Guided Surgery.平板探测器锥形束CT:从影像科学到影像引导手术
Nucl Instrum Methods Phys Res A. 2011 Aug 21;648(S1):S241-S250. doi: 10.1016/j.nima.2010.11.088.
2
Automatic localization of vertebral levels in x-ray fluoroscopy using 3D-2D registration: a tool to reduce wrong-site surgery.基于 3D-2D 配准的 X 射线透视下椎体自动定位:一种减少错误手术部位的工具。
Phys Med Biol. 2012 Sep 7;57(17):5485-508. doi: 10.1088/0031-9155/57/17/5485. Epub 2012 Aug 3.
3
An electromagnetic "Tracker-in-Table" configuration for X-ray fluoroscopy and cone-beam CT-guided surgery.一种用于 X 射线透视和锥形束 CT 引导手术的电磁“表中跟踪器”配置。
Int J Comput Assist Radiol Surg. 2013 Jan;8(1):1-13. doi: 10.1007/s11548-012-0744-z. Epub 2012 May 15.
4
Automatic tracking of implanted fiducial markers in cone beam CT projection images.锥形束 CT 投影图像中植入基准标记的自动跟踪。
Med Phys. 2012 Mar;39(3):1322-34. doi: 10.1118/1.3684959.
5
Robust automatic segmentation of multiple implanted cylindrical gold fiducial markers in cone-beam CT projections.锥形束 CT 投影中多个植入圆柱形金基准标记的稳健自动分割。
Med Phys. 2011 Dec;38(12):6351-61. doi: 10.1118/1.3658566.
6
Mobile C-arm cone-beam CT for guidance of spine surgery: image quality, radiation dose, and integration with interventional guidance.移动式 C 臂锥形束 CT 引导脊柱手术:图像质量、辐射剂量和与介入引导的整合。
Med Phys. 2011 Aug;38(8):4563-74. doi: 10.1118/1.3597566.
7
TREK: an integrated system architecture for intraoperative cone-beam CT-guided surgery.TREK:一种用于术中锥形束 CT 引导手术的集成系统架构。
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A method for robust segmentation of arbitrarily shaped radiopaque structures in cone-beam CT projections.一种用于在锥形束 CT 投影中对任意形状的不透射线结构进行稳健分割的方法。
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An algorithm to extract three-dimensional motion by marker tracking in the kV projections from an on-board imager: four-dimensional cone-beam CT and tumor tracking implications.一种基于机载影像系统千伏投影中标记点跟踪提取三维运动的算法:四维锥形束 CT 和肿瘤跟踪的意义。
J Appl Clin Med Phys. 2011 Feb 1;12(2):3407. doi: 10.1120/jacmp.v12i2.3407.
10
Evaluation of spherical fiducial localization in C-arm cone-beam CT using patient data.使用患者数据评估 C 臂锥形束 CT 中的球形基准定位。
Med Phys. 2010 Oct;37(10):5298-305. doi: 10.1118/1.3475941.

用于锥形束 CT 介入引导中自动图像到世界配准的稳健方法。

Robust methods for automatic image-to-world registration in cone-beam CT interventional guidance.

机构信息

Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21202, USA.

出版信息

Med Phys. 2012 Oct;39(10):6484-98. doi: 10.1118/1.4754589.

DOI:10.1118/1.4754589
PMID:23039683
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3477200/
Abstract

PURPOSE

Real-time surgical navigation relies on accurate image-to-world registration to align the coordinate systems of the image and patient. Conventional manual registration can present a workflow bottleneck and is prone to manual error and intraoperator variability. This work reports alternative means of automatic image-to-world registration, each method involving an automatic registration marker (ARM) used in conjunction with C-arm cone-beam CT (CBCT). The first involves a Known-Model registration method in which the ARM is a predefined tool, and the second is a Free-Form method in which the ARM is freely configurable.

METHODS

Studies were performed using a prototype C-arm for CBCT and a surgical tracking system. A simple ARM was designed with markers comprising a tungsten sphere within infrared reflectors to permit detection of markers in both x-ray projections and by an infrared tracker. The Known-Model method exercised a predefined specification of the ARM in combination with 3D-2D registration to estimate the transformation that yields the optimal match between forward projection of the ARM and the measured projection images. The Free-Form method localizes markers individually in projection data by a robust Hough transform approach extended from previous work, backprojected to 3D image coordinates based on C-arm geometric calibration. Image-domain point sets were transformed to world coordinates by rigid-body point-based registration. The robustness and registration accuracy of each method was tested in comparison to manual registration across a range of body sites (head, thorax, and abdomen) of interest in CBCT-guided surgery, including cases with interventional tools in the radiographic scene.

RESULTS

The automatic methods exhibited similar target registration error (TRE) and were comparable or superior to manual registration for placement of the ARM within ∼200 mm of C-arm isocenter. Marker localization in projection data was robust across all anatomical sites, including challenging scenarios involving the presence of interventional tools. The reprojection error of marker localization was independent of the distance of the ARM from isocenter, and the overall TRE was dominated by the configuration of individual fiducials and distance from the target as predicted by theory. The median TRE increased with greater ARM-to-isocenter distance (e.g., for the Free-Form method, TRE increasing from 0.78 mm to 2.04 mm at distances of ∼75 mm and 370 mm, respectively). The median TRE within ∼200 mm distance was consistently lower than that of the manual method (TRE = 0.82 mm). Registration performance was independent of anatomical site (head, thorax, and abdomen). The Free-Form method demonstrated a statistically significant improvement (p = 0.0044) in reproducibility compared to manual registration (0.22 mm versus 0.30 mm, respectively).

CONCLUSIONS

Automatic image-to-world registration methods demonstrate the potential for improved accuracy, reproducibility, and workflow in CBCT-guided procedures. A Free-Form method was shown to exhibit robustness against anatomical site, with comparable or improved TRE compared to manual registration. It was also comparable or superior in performance to a Known-Model method in which the ARM configuration is specified as a predefined tool, thereby allowing configuration of fiducials on the fly or attachment to the patient.

摘要

目的

实时手术导航依赖于精确的图像到世界配准,以对齐图像和患者的坐标系。传统的手动配准可能会成为工作流程的瓶颈,并且容易出现手动错误和操作员内变异性。这项工作报告了自动图像到世界配准的替代方法,每种方法都涉及与 C 臂锥形束 CT(CBCT)结合使用的自动配准标记(ARM)。第一种方法是使用已知模型的配准方法,其中 ARM 是预定义的工具,第二种方法是自由形态方法,其中 ARM 是可自由配置的。

方法

使用 CBCT 的原型 C 臂和手术跟踪系统进行了研究。设计了一个简单的 ARM,其标记由钨球和红外反射器组成,以允许在 X 射线投影和红外跟踪器中检测到标记。已知模型方法通过 3D-2D 配准来使用 ARM 的预定义规范来估计变换,该变换产生 ARM 的正向投影与测量投影图像之间的最佳匹配。自由形态方法通过从以前的工作扩展的稳健霍夫变换方法在投影数据中单独定位标记,并根据 C 臂几何校准将其反向投影到 3D 图像坐标。通过刚体基于点的配准将图像域点集转换为世界坐标。在 CBCT 引导手术中对感兴趣的各种身体部位(头部、胸部和腹部)进行了测试,包括在射线场景中存在介入工具的情况,比较了每种方法与手动配准的鲁棒性和配准准确性。

结果

自动方法的目标注册误差(TRE)相似,并且在将 ARM 放置在距 C 臂等中心约 200mm 范围内时,与手动配准相当或优于手动配准。在所有解剖部位(包括涉及介入工具的具有挑战性的场景)中,标记在投影数据中的定位都具有稳健性。标记定位的重投影误差与 ARM 与等中心的距离无关,并且总体 TRE 主要由个体基准的配置和理论预测的目标距离决定。随着 ARM 与等中心距离的增加(例如,对于自由形态方法,在距离约为 75mm 和 370mm 时,TRE 分别从 0.78mm 增加到 2.04mm),TRE 中位数增加。在距离约 200mm 内,TRE 始终低于手动方法(TRE=0.82mm)。注册性能与解剖部位(头部、胸部和腹部)无关。自由形态方法与手动注册相比,在可重复性方面表现出显著改善(p=0.0044)(分别为 0.22mm 和 0.30mm)。

结论

自动图像到世界配准方法在 CBCT 引导手术中显示出提高准确性、可重复性和工作流程的潜力。已经证明自由形态方法具有针对解剖部位的稳健性,与手动配准相比,TRE 具有可比性或改善。与 ARM 配置指定为预定义工具的已知模型方法相比,它在性能上也具有可比性或优势,从而可以即时配置基准或连接到患者。