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Laser range scanning for image-guided neurosurgery: Investigation of image-to-physical space registrations

机译:用于图像引导的神经外科手术的激光范围扫描:图像到物理空间配准的研究

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摘要

In this article a comprehensive set of registration methods is utilized to provide image-to-physical space registration for image-guided neurosurgery in a clinical study. Central to all methods is the use of textured point clouds as provided by laser range scanning technology. The objective is to perform a systematic comparison of registration methods that include both extracranial (skin marker point-based registration (PBR), and face-based surface registration) and intracranial methods (feature PBR, cortical vessel-contour registration, a combined geometry∕intensity surface registration method, and a constrained form of that method to improve robustness). The platform facilitates the selection of discrete soft-tissue landmarks that appear on the patient’s intraoperative cortical surface and the preoperative gadolinium-enhanced magnetic resonance (MR) image volume, i.e., true corresponding novel targets. In an 11 patient study, data were taken to allow statistical comparison among registration methods within the context of registration error. The results indicate that intraoperative face-based surface registration is statistically equivalent to traditional skin marker registration. The four intracranial registration methods were investigated and the results demonstrated a target registration error of 1.6±0.5 mm, 1.7±0.5 mm, 3.9±3.4 mm, and 2.0±0.9 mm, for feature PBR, cortical vessel-contour registration, unconstrained geometric∕intensity registration, and constrained geometric∕intensity registration, respectively. When analyzing the results on a per case basis, the constrained geometric∕intensity registration performed best, followed by feature PBR, and finally cortical vessel-contour registration. Interestingly, the best target registration errors are similar to targeting errors reported using bone-implanted markers within the context of rigid targets. The experience in this study as with others is that brain shift can compromise extracranial registration methods from the earliest stages. Based on the results reported here, organ-based approaches to registration would improve this, especially for shallow lesions.
机译:在本文中,一套完整的配准方法用于为临床研究中的图像引导神经外科手术提供图像到物理空间的配准。所有方法的核心是使用激光测距技术提供的纹理点云。目的是对包括颅外(基于皮肤标记点的注册(PBR)和基于面部的表面注册)和颅内方法(功能性PBR,皮质血管轮廓注册,组合的几何形状)在内的注册方法进行系统的比较。强度表面配准方法,以及该方法的约束形式以提高鲁棒性)。该平台有助于选择出现在患者术中皮质表面上的离散软组织界标和术前g增强磁共振(MR)图像量,即真正对应的新型靶标。在一项针对11位患者的研究中,采用了数据以允许在注册错误的情况下对注册方法进行统计比较。结果表明,术中基于面部的表面注册在统计学上等同于传统的皮肤标记注册。研究了四种颅内套准方法,结果显示特征PBR,皮质血管轮廓注册,几何形状不受限制的目标套准误差为1.6±0.5 mm,1.7±0.5 mm,3.9±3.4 mm和2.0±0.9 mm。强度配准和受约束的几何强度配准。在每个案例的基础上分析结果时,受约束的几何强度配准效果最佳,其次是特征PBR,最后是皮质血管轮廓轮廓配准。有趣的是,最佳目标配准错误类似于在刚性目标的背景下使用骨植入标记物报告的目标错误。与其他研究一样,本研究的经验是,从最早的阶段开始,脑部移位会损害颅外注册方法。根据此处报告的结果,基于器官的注册方法将改善这种情况,尤其是对于浅部病变。

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