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The distribution of registration error of a fiducial marker in rigid-body point-based registration

机译:基于刚体点的注册中基准标记的注册误差分布

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Many image-guidance surgical systems rely on rigid-body, point-based registration of fiducial markers attached to the patient. Marker locations in image space and physical space are used to provide the transformation that maps a point from one space to the other. Target registration error (TRE) is known to depend on the fiducial localization error (FLE), and the fiducial registration error (FRE) of a set of markers, though a poor predictor of TRE, is a useful predictor of FLE. All fiducials are typically weighted equally for registration purposes, but is also a common practice to ignore a marker at position r by zeroing its weight when its individual error, FRE(r), is high in an effort to reduce TRE. The idea is that such markers are likely to have been compromised, i.e., perturbed badly between imaging and surgery. While ignoring a compromised marker may indeed reduce TRE, the expected effect of ignoring an uncompromised marker is to increase TRE. There is unfortunately no established method for deciding whether a given marker is likely to have been compromised. In order to make this decision, it is necessary to know the probability distribution p>(FRE(r)), which has not been heretofore determined. With such a distribution, it may be possible to identify a compromised marker and to adjust its weight in order to improve the expected TRE. In this paper we derive an approximate formula for p(FRE(r)) accurate to first order in FLE. We show by means of numerical simulations that the approximation is valid.
机译:许多图像引导外科系统依赖于刚体,基于点的基于点的基准标记的登记。图像空间和物理空间中的标记位置用于提供从一个空间映射到另一个空间的一个变换。众所周知,目标登记错误(TRE)取决于基准定位错误(FLE),并且一组标记的基准登记错误(FRE)虽然TRE的可预测器,是一个有用的飞行预测因子。所有基准均基准通常同样加权用于登记目的,但是在其单独的错误(R)时,通过归零其重量,忽略其重量的常见做法是忽略它的重量,以减少TRE。这个想法是,这种标记可能被妥协,即,在成像和手术之间严重扰乱。虽然忽略受损标记物确实可以减少TRE,但忽略不妥协的标记的预期效果是增加TRE。遗憾的是,没有建立关于给定标记是否可能受到损害的方法。为了做出这一决定,有必要知道概率分布P>(FRE(R)),其尚未确定迄今为止。利用这种分布,可以识别受损标记物并调节其重量以改善预期的TRE。在本文中,我们获得了P(FRE(R))的近似公式,准确到FLE中的第一顺序。我们通过数值模拟显示近似有效的数值模拟。

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