去相关
计算机科学
分辨率(逻辑)
图像处理
衍射
图像(数学)
图像分辨率
人工智能
计算机视觉
显微镜
自相关
极限(数学)
生物系统
光学
数学
物理
统计
生物
数学分析
作者
A. Descloux,Kristin S. Grußmayer,Aleksandra Rađenović
出处
期刊:Nature Methods
[Springer Nature]
日期:2019-08-26
卷期号:16 (9): 918-924
被引量:279
标识
DOI:10.1038/s41592-019-0515-7
摘要
Super-resolution microscopy opened diverse new avenues of research by overcoming the resolution limit imposed by diffraction. Exploitation of the fluorescent emission of individual fluorophores made it possible to reveal structures beyond the diffraction limit. To accurately determine the resolution achieved during imaging is challenging with existing metrics. Here, we propose a method for assessing the resolution of individual super-resolved images based on image partial phase autocorrelation. The algorithm is model-free and does not require any user-defined parameters. We demonstrate its performance on a wide variety of imaging modalities, including diffraction-limited techniques. Finally, we show how our method can be used to optimize image acquisition and post-processing in super-resolution microscopy. Decorrelation analysis offers an improved method for assessing image resolution that works on a single image and is insensitive to common image artifacts. The method can be applied generally to any type of microscopy images.
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