LaViolette Aaron K, Xu Chris
School of Applied and Engineering Physics, Cornell University, Ithaca NY 14853, USA.
Biomed Opt Express. 2021 Oct 20;12(11):7033-7048. doi: 10.1364/BOE.442442. eCollection 2021 Nov 1.
Much of fluorescence-based microscopy involves detection of if an object is present or absent (i.e., binary detection). The imaging depth of three-dimensionally resolved imaging, such as multiphoton imaging, is fundamentally limited by out-of-focus background fluorescence, which when compared to the in-focus fluorescence makes detecting objects in the presence of noise difficult. Here, we use detection theory to present a statistical framework and metric to quantify the quality of an image when binary detection is of interest. Our treatment does not require acquired or reference images, and thus allows for a theoretical comparison of different imaging modalities and systems.
基于荧光的显微镜成像大多涉及检测物体是否存在（即二元检测）。三维分辨成像（如多光子成像）的成像深度从根本上受到离焦背景荧光的限制，与聚焦荧光相比，这使得在存在噪声的情况下检测物体变得困难。在这里，我们运用检测理论提出一个统计框架和度量标准，以在二元检测受到关注时量化图像质量。我们的方法不需要采集的图像或参考图像，因此可以对不同的成像模式和系统进行理论比较。
