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一项使用三维分辨率测量方法对高分辨率显微镜成像模式的比较研究。

A comparative study of high resolution microscopy imaging modalities using a three-dimensional resolution measure.

作者信息

Chao Jerry, Ram Sripad, Ward E Sally, Ober Raimund J

机构信息

Department of Electrical Engineering, University of Texas at Dallas, Richardson, TX 75080, USA.

出版信息

Opt Express. 2009 Dec 21;17(26):24377-402. doi: 10.1364/OE.17.024377.

Abstract

From an acquired image, single molecule microscopy makes possible the determination of the distance separating two closely spaced biomolecules in three-dimensional (3D) space. Such distance information can be an important indicator of the nature of the biomolecular interaction. Distance determination, however, is especially difficult when, for example, the imaged point sources are very close to each other or are located near the focal plane of the imaging setup. In the context of such challenges, we compare the limits of the distance estimation accuracy for several high resolution 3D imaging modalities. The comparisons are made using a Cramer-Rao lower bound-based 3D resolution measure which predicts the best possible accuracy with which a given distance can be estimated. Modalities which separate the detection of individual point sources (e.g., using photoactivatable fluorophores) are shown to provide the best accuracy limits when the two point sources are very close to each other and/or are oriented near parallel to the optical axis. Meanwhile, modalities which implement the simultaneous imaging of the point sources from multiple focal planes perform best when given a near-focus point source pair. We also demonstrate that the maximum likelihood estimator is capable of attaining the limit of the accuracy predicted for each modality.

摘要

从获取的图像中,单分子显微镜能够确定三维(3D)空间中两个紧密间隔的生物分子之间的距离。这种距离信息可能是生物分子相互作用性质的重要指标。然而,例如当成像的点源彼此非常接近或位于成像装置的焦平面附近时,距离测定尤其困难。在这些挑战的背景下,我们比较了几种高分辨率3D成像模式的距离估计精度极限。使用基于克拉美-罗下界的3D分辨率度量进行比较,该度量预测了估计给定距离时可能达到的最佳精度。当两个点源彼此非常接近和/或其方向接近平行于光轴时,分离单个点源检测的模式(例如使用光激活荧光团)显示出提供最佳精度极限。同时,当给定一对近焦点源时,从多个焦平面同时成像点源的模式表现最佳。我们还证明了最大似然估计器能够达到为每种模式预测的精度极限。

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