论文标题
学习用于超密集3D定位显微镜的最佳PSF对
Learning an optimal PSF-pair for ultra-dense 3D localization microscopy
论文作者
论文摘要
多粒子跟踪中的长期挑战是在紧邻近端的单个颗粒的准确，精确的3D定位。快照3D成像的一种已建立的方法是点传播功能（PSF）工程，其中修改PSF以编码轴向信息。但是，由于横向PSF重叠，工程的PSF在高密度上的本地化挑战。在这里，我们建议同时使用多个PSF来帮助克服这一挑战，并研究为密集的3D定位设计多个PSF的问题。我们使用分叉的光学系统实施我们的方法，该光学系统修改两个单独的PSF，并使用三种不同的方法（包括端到端学习）设计PSF。我们通过对细胞中荧光标记的端粒标记的体积成像进行实验证明我们的方法。
A long-standing challenge in multiple-particle-tracking is the accurate and precise 3D localization of individual particles at close proximity. One established approach for snapshot 3D imaging is point-spread-function (PSF) engineering, in which the PSF is modified to encode the axial information. However, engineered PSFs are challenging to localize at high densities due to lateral PSF overlaps. Here we suggest using multiple PSFs simultaneously to help overcome this challenge, and investigate the problem of engineering multiple PSFs for dense 3D localization. We implement our approach using a bifurcated optical system that modifies two separate PSFs, and design the PSFs using three different approaches including end-to-end learning. We demonstrate our approach experimentally by volumetric imaging of fluorescently labelled telomeres in cells.
