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图像引导神经外科中最小目标配准误差的基准优化。

Fiducial optimization for minimal target registration error in image-guided neurosurgery.

机构信息

Rachel and Selim Benin School of Engineering and Computer Science, The Hebrew University of Jerusalem, Jerusalem, Israel.

出版信息

IEEE Trans Med Imaging. 2012 Mar;31(3):725-37. doi: 10.1109/TMI.2011.2175939. Epub 2011 Dec 6.


DOI:10.1109/TMI.2011.2175939
PMID:22156977
Abstract

This paper presents new methods for the optimal selection of anatomical landmarks and optimal placement of fiducial markers in image-guided neurosurgery. These methods allow the surgeon to optimally plan fiducial marker locations on routine diagnostic images before preoperative imaging and to intraoperatively select the set of fiducial markers and anatomical landmarks that minimize the expected target registration error (TRE). The optimization relies on a novel empirical simulation-based TRE estimation method built on actual fiducial localization error (FLE) data. Our methods take the guesswork out of the registration process and can reduce localization error without additional imaging and hardware. Our clinical experiments on five patients who underwent brain surgery with a navigation system show that optimizing one marker location and the anatomical landmarks configuration reduced the TRE. The average TRE values using the usual fiducials setup and using the suggested method were 4.7 mm and 3.2 mm, respectively. We observed a maximum improvement of 4 mm. Reducing the target registration error has the potential to support safer and more accurate minimally invasive neurosurgical procedures.

摘要

本文提出了在图像引导神经外科中优化选择解剖标志和最佳放置基准标记的新方法。这些方法允许外科医生在术前成像之前在常规诊断图像上最优地规划基准标记位置,并在术中选择最小化预期目标注册误差 (TRE) 的基准标记和解剖标志集。优化依赖于一种新颖的基于经验模拟的 TRE 估计方法,该方法建立在实际基准定位误差 (FLE) 数据之上。我们的方法消除了注册过程中的猜测,并可以在不增加成像和硬件的情况下减少定位误差。我们对五名接受导航系统辅助脑外科手术的患者进行的临床实验表明,优化一个标记位置和解剖标志配置可以降低 TRE。使用常用基准标记设置和建议方法的平均 TRE 值分别为 4.7 毫米和 3.2 毫米,我们观察到最大改善为 4 毫米。降低目标注册误差有可能支持更安全、更精确的微创神经外科手术。

相似文献

[1]
Fiducial optimization for minimal target registration error in image-guided neurosurgery.

IEEE Trans Med Imaging. 2011-12-6

[2]
Fiducial markers configuration optimization in image-guided surgery.

Biomed Mater Eng. 2014

[3]
Improving target registration accuracy in image-guided neurosurgery by optimizing the distribution of fiducial points.

Int J Med Robot. 2009-3

[4]
Anatomical landmarks for point-matching registration in image-guided neurosurgery.

Int J Med Robot. 2013-6-3

[5]
Predicting error in rigid-body point-based registration.

IEEE Trans Med Imaging. 1998-10

[6]
Distribution templates of the fiducial points in image-guided neurosurgery.

Neurosurgery. 2010-3

[7]
Geometrical analysis of registration errors in point-based rigid-body registration using invariants.

Med Image Anal. 2010-8-10

[8]
Minimization of target registration error for vertebra in image-guided spine surgery.

Int J Comput Assist Radiol Surg. 2013-7-3

[9]
Intraoperative fiducial-less patient registration using volumetric 3D ultrasound: a prospective series of 32 neurosurgical cases.

J Neurosurg. 2015-9

[10]
Application accuracy in frameless image-guided neurosurgery: a comparison study of three patient-to-image registration methods.

J Neurosurg. 2007-6

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[2]
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APL Bioeng. 2024-4-1

[3]
Differential Image Based Robot to MRI Scanner Registration with Active Fiducial Markers for an MRI-Guided Robotic Catheter System.

Rep U S. 2020-10

[4]
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IEEE Trans Med Imaging. 2021-4

[5]
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J Med Syst. 2020-3-9

[6]
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Sensors (Basel). 2020-2-28

[7]
Soft tissue deformation tracking by means of an optimized fiducial marker layout with application to cancer tumors.

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[8]
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Int J Comput Assist Radiol Surg. 2018-10-13

[9]
An Augmented Reality System Using Improved-Iterative Closest Point Algorithm for On-Patient Medical Image Visualization.

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[10]
Orientation Uncertainty Characteristics of Some Pose Measuring Systems.

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