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通过空间可变点扩散函数生成实现大视场三维定位显微镜技术

Large-FOV 3D localization microscopy by spatially variant point spread function generation.

作者信息

Xiao Dafei, Kedem Orange Reut, Opatovski Nadav, Parizat Amit, Nehme Elias, Alalouf Onit, Shechtman Yoav

机构信息

Russell Berrie Nanotechnology Institute, Technion-Israel Institute of Technology, Haifa, Israel.

Department of Biomedical Engineering, Technion-Israel Institute of Technology, Haifa, Israel.

出版信息

Sci Adv. 2024 Mar 8;10(10):eadj3656. doi: 10.1126/sciadv.adj3656.

Abstract

Accurate characterization of the microscopic point spread function (PSF) is crucial for achieving high-performance localization microscopy (LM). Traditionally, LM assumes a spatially invariant PSF to simplify the modeling of the imaging system. However, for large fields of view (FOV) imaging, it becomes important to account for the spatially variant nature of the PSF. Here, we propose an accurate and fast principal components analysis-based field-dependent 3D PSF generator (PPG3D) and localizer for LM. Through simulations and experimental three-dimensional (3D) single-molecule localization microscopy (SMLM), we demonstrate the effectiveness of PPG3D, enabling super-resolution imaging of mitochondria and microtubules with high fidelity over a large FOV. A comparison of PPG3D with a shift-variant PSF generator for 3D LM reveals a threefold improvement in accuracy. Moreover, PPG3D is approximately 100 times faster than existing PSF generators, when used in image plane-based interpolation mode. Given its user-friendliness, we believe that PPG3D holds great potential for widespread application in SMLM and other imaging modalities.

摘要

精确表征微观点扩散函数(PSF)对于实现高性能定位显微镜(LM)至关重要。传统上,LM假定PSF在空间上是不变的,以简化成像系统的建模。然而,对于大视野(FOV)成像,考虑PSF的空间变化特性变得很重要。在此,我们提出了一种基于主成分分析的精确且快速的场依赖型3D PSF生成器(PPG3D)以及用于LM的定位器。通过模拟和实验性三维(3D)单分子定位显微镜(SMLM),我们证明了PPG3D的有效性,能够在大FOV上以高保真度对线粒体和微管进行超分辨率成像。将PPG3D与用于3D LM的位移可变PSF生成器进行比较,结果显示在精度上提高了三倍。此外,当以基于图像平面的插值模式使用时,PPG3D比现有的PSF生成器快约100倍。鉴于其用户友好性,我们相信PPG3D在SMLM和其他成像模式中具有广泛应用的巨大潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/507c/10923516/894db9d8b8e4/sciadv.adj3656-f1.jpg

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