Resolution beyond Rayleigh's criterion: a modern resolution measure with applications to single molecule imaging

S. Ram, P. Prabhat, J. Chao, E. Ward, R. Ober
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引用次数: 1

Abstract

Rayleigh's criterion, although extensively used, is well known to be based on heuristic notions that are inadequate for modern optical microscopy applications. This inadequacy has necessitated a reassessment of the resolution limits of optical microscopes. By adopting a stochastic framework and using the statistical theory concerning the Fisher information matrix, we have derived a new resolution measure that overcomes the limitations of Rayleigh's criterion. Here, we provide a brief overview of this and other related results published by our group. The new resolution measure predicts that there is no resolution limit, but that the resolvability depends on the number of detected photons. It has been experimentally verified that distances well below Rayleigh's limit can be measured from images of closely spaced single molecules with an accuracy as predicted by the new resolution measure. The stochastic framework used to obtain the new resolution measure is applicable to a wide variety of estimation problems encountered in optical microscopy. As an application, we have investigated the localization accuracy problem, which is concerned with how accurately the 2D/3D location of a microscopic object can determined from its image. One of the shortcomings of current microscopy techniques is that they suffer from poor depth discrimination and as a result they are not well adapted for 3D tracking of single molecules/particles. We have recently developed a novel imaging modality called multifocal plane microscopy (MUM) to overcome this limitation. Using the stochastic framework, we have shown that MUM has significantly improved depth discrimination, which in turn enables 3D single particle tracking at high axial localization accuracy.
超越瑞利准则的分辨率:一种应用于单分子成像的现代分辨率测量
瑞利的标准,虽然广泛使用,是众所周知的是基于启发式的概念是不够的现代光学显微镜的应用。这方面的不足使人们有必要重新评估光学显微镜的分辨率极限。本文采用随机框架,利用Fisher信息矩阵的统计理论,推导了一种克服瑞利准则局限性的分辨率度量方法。在这里,我们简要概述了这一结果以及我们小组发表的其他相关结果。新的分辨率测量预测没有分辨率限制,但分辨率取决于探测到的光子的数量。实验证明,距离远低于瑞利极限的距离可以从距离很近的单分子图像中测量出来,其精度与新分辨率测量方法所预测的一致。用于获得新分辨率度量的随机框架适用于光学显微镜中遇到的各种估计问题。作为一个应用,我们研究了定位精度问题,即如何准确地从其图像中确定微观物体的二维/三维位置。当前显微镜技术的缺点之一是它们的深度辨别能力差,因此它们不能很好地适应于单个分子/粒子的3D跟踪。我们最近开发了一种新的成像方式,称为多焦平面显微镜(MUM),以克服这一限制。使用随机框架,我们已经证明MUM显著改善了深度识别,从而实现了高轴向定位精度的3D单粒子跟踪。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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