Rethinking resolution estimation in fluorescence microscopy: from theoretical resolution criteria to super-resolution microscopy

Abstract

Resolution is undoubtedly the most important parameter in optical microscopy by providing an estimation on the maximum resolving power of a certain optical microscope. For centuries, the resolution of an optical microscope is generally considered to be limited only by the numerical aperture of the optical system and the wavelength of light. However, since the invention and popularity of various advanced fluorescence microscopy techniques, especially super-resolution fluorescence microscopy, many new methods have been proposed for estimating the resolution, leading to confusions for researchers who need to quantify the resolution of their fluorescence microscopes. In this paper, we firstly summarize the early concepts and criteria for predicting the resolution limit of an ideal optical system. Then, we discuss some important influence factors that deteriorate the resolution of a certain fluorescence microscope. Finally, we provide methods and examples on how to measure the resolution of a fluorescence microscope from captured fluorescence images. This paper aims to answer as best as possible the theoretical and practical issues regarding the resolution estimation in fluorescence microscopy.

Accelerated protein retention expansion microscopy using microwave radiation

“…6E-6F). Resolution is characterized as the minimum distance between two points on a sample that can be identified as distinct entities by an optical system (Li & Huang 2020). Since the separation between two points of signal will produce a decreased area under the curve (AUC) in a linear ROI, we thus quantified the area under the curve (AUC) in normalized intensity plots across multiple linear ROIs in single optical images from the M/W ExM-expanded and the non-expanded brain tissue as a readout for resolution.…”

“…6C-6C').Additionally, individual Scribble puncta are much better resolved in confocal images from M/W ExM-processed brain tissue (Fig.6D-6D') than in the non-expanded images (Fig.6C-6C'), which can also be seen in the intensity plots drawn across neighboring Scribble puncta (Fig.6E-6F). Resolution is characterized as the minimum distance between two points on a sample that can be identified as distinct entities by an optical system(Li & Huang 2020). Since the separation between two points of signal will produce a decreased area under the curve (AUC) in a linear ROI, we thus quantified the area under the curve (AUC) in normalized intensity plots across multiple linear ROIs in single optical images from the M/W ExM-expanded and the non-expanded brain tissue as a readout for resolution.…”

光学显微图像定量评价方法及应用研究进展（特邀）

“…通信作者： * wenjieliu@zju.edu.cn 1 Example of the Gaussian fitting and Airy disk corresponding to the point spread function (PSF) [19] 0618013 -3 corresponding filtering of the image [24] ; (b) correlation between the Fourier transforms of the two independent images over the perimeter of the circle with radius q is calculated resulting in a FRC curve indicating the decay of the correlation with spatial frequency increasing, the scale bar is 1 μm [27] ; (c) illustration for single image FRC [25] 图 3 免疫荧光标记的果蝇巨噬细胞微管的传统和超分辨显微图像， 比例尺为 5 μm， 插图里的比例尺为 0. 5 Workflow of image decorrelation resolution analysis [33]…”