Wang Famin, Li Hangfeng, Xiao Yun, Zhao Mengyuan, Zhang YunHai
Opt Lett. 2022 Jan 1;47(1):182-185. doi: 10.1364/OL.446947.
We propose an optimization algorithm based on Fresnel approximation (FA) imaging to optimize an extended-axial-depth point spread function (PSF) for 3D particle localization. The transfer function efficiency of the PSF is improved by repeatedly imposing constraints in the object plane, the spatial domain, and the Fourier domain. During the iterative calculation, the effective photon number or Cramer-Rao lower bound is used as the termination condition of the iteration. The algorithm allows flexible adjustment of the peak intensity ratio of the two main lobes. Moreover, the transfer function efficiency can be balanced by increasing the weight of the modulation function of the expected PSF at each axial position. The twin-Airy (TA) PSF optimized by the FA optimization algorithm does not require complex post-processing, whereas post-processing is an essential step for the unoptimized TA-PSF. The optimization algorithm is significant for extended-axial-depth PSFs used for 3D particle localization, as it improves localization precision and temporal resolution.
我们提出一种基于菲涅耳近似(FA)成像的优化算法,以优化用于三维粒子定位的扩展轴向深度点扩散函数(PSF)。通过在物平面、空间域和傅里叶域中反复施加约束,提高了PSF的传递函数效率。在迭代计算过程中,使用有效光子数或克拉美 - 罗下界作为迭代的终止条件。该算法允许灵活调整两个主瓣的峰值强度比。此外,通过增加预期PSF在每个轴向位置的调制函数的权重,可以平衡传递函数效率。通过FA优化算法优化的双艾里(TA)PSF不需要复杂的后处理,而对于未优化的TA - PSF,后处理是必不可少的步骤。该优化算法对于用于三维粒子定位的扩展轴向深度PSF具有重要意义,因为它提高了定位精度和时间分辨率。