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基于梯度拟合的快速精确三维荧光团定位

Fast and Precise 3D Fluorophore Localization based on Gradient Fitting.

作者信息

Ma Hongqiang, Xu Jianquan, Jin Jingyi, Gao Ying, Lan Li, Liu Yang

机构信息

Biomedical and Optical Imaging Laboratory, Departments of Medicine and Bioengineering, University of Pittsburgh, Pittsburgh PA 15213, USA.

School of Medicine, Tsinghua University, China.

出版信息

Sci Rep. 2015 Sep 22;5:14335. doi: 10.1038/srep14335.

Abstract

Astigmatism imaging approach has been widely used to encode the fluorophore's 3D position in single-particle tracking and super-resolution localization microscopy. Here, we present a new high-speed localization algorithm based on gradient fitting to precisely decode the 3D subpixel position of the fluorophore. This algebraic algorithm determines the center of the fluorescent emitter by finding the position with the best-fit gradient direction distribution to the measured point spread function (PSF), and can retrieve the 3D subpixel position of the fluorophore in a single iteration. Through numerical simulation and experiments with mammalian cells, we demonstrate that our algorithm yields comparable localization precision to the traditional iterative Gaussian function fitting (GF) based method, while exhibits over two orders-of-magnitude faster execution speed. Our algorithm is a promising high-speed analyzing method for 3D particle tracking and super-resolution localization microscopy.

摘要

散光成像方法已广泛应用于单粒子追踪和超分辨率定位显微镜中,用于编码荧光团的三维位置。在此,我们提出一种基于梯度拟合的新型高速定位算法,以精确解码荧光团的三维亚像素位置。这种代数算法通过找到与测量的点扩散函数(PSF)的最佳拟合梯度方向分布的位置来确定荧光发射体的中心,并且可以在单次迭代中检索荧光团的三维亚像素位置。通过数值模拟和对哺乳动物细胞的实验,我们证明我们的算法产生的定位精度与基于传统迭代高斯函数拟合(GF)的方法相当,同时执行速度快两个数量级以上。我们的算法是一种有前途的用于三维粒子追踪和超分辨率定位显微镜的高速分析方法。

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