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A Robust Statistical Estimation (RoSE) algorithm jointly recovers the 3D location and intensity of single molecules accurately and precisely

机译:稳健的统计估计(RoSE)算法可共同,准确地恢复单个分子的3D位置和强度

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摘要

In single-molecule (SM) super-resolution microscopy, the complexity of a biological structure, high molecular density, and a low signal-to-background ratio (SBR) may lead to imaging artifacts without a robust localization algorithm. Moreover, engineered point spread functions (PSFs) for 3D imaging pose difficulties due to their intricate features. We develop a Robust Statistical Estimation algorithm, called RoSE, that enables joint estimation of the 3D location and photon counts of SMs accurately and precisely using various PSFs under conditions of high molecular density and low SBR.
机译:在单分子(SM)超分辨率显微镜中,生物结构的复杂性,高分子密度和低信噪比(SBR)可能导致没有稳固的定位算法的成像伪像。此外,由于其复杂的功能,用于3D成像的工程化点扩散函数(PSF)带来了困难。我们开发了一种称为RoSE的鲁棒统计估计算法,该算法可在高分子密度和低SBR条件下使用各种PSF精确,精确地联合估计SM的3D位置和光子数。

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