The resolution of single molecule localization imaging techniques largely depends on the precision of localization algorithms.However,the commonly used Gaussian function is not appropriate for anisotropic dipoles beca...The resolution of single molecule localization imaging techniques largely depends on the precision of localization algorithms.However,the commonly used Gaussian function is not appropriate for anisotropic dipoles because it is not the true point spread function.We derived the theoretical point spread function of tilted dipoles with restricted mobility and developed an algorithm based on an artifi cial neural network for estimating the localization,orientation and mobility of individual dipoles.Compared with fi tting-based methods,our algorithm demonstrated ultrafast speed and higher accuracy,reduced sensitivity to defocusing,strong robustness and adaptability,making it an optimal choice for both two-dimensional and threedimensional super-resolution imaging analysis.展开更多
基金We thank L.L.Looger(Janelia Farm Research Campus)for providing the mEos2 cDNA and Toshio Yanagida(Osaka University,Japan)for sharing the Q rods.This work was supported by grants from the National Basic Research Program(973 Program)(Nos.2010CB833701 and 2010CB912303)the National Key Technology R&D Program(SQ2011SF11B01041)+2 种基金the National Natural Science Foundation of China(Grant Nos.31130065,31170818,90913022,31127901,and 31100615)the Beijing Natural Science Foundation(7121008)the Chinese Academy of Sciences Project(KSCX1-1W-J-3,KSCX2-EWQ-11,and 2009-154-27).
文摘The resolution of single molecule localization imaging techniques largely depends on the precision of localization algorithms.However,the commonly used Gaussian function is not appropriate for anisotropic dipoles because it is not the true point spread function.We derived the theoretical point spread function of tilted dipoles with restricted mobility and developed an algorithm based on an artifi cial neural network for estimating the localization,orientation and mobility of individual dipoles.Compared with fi tting-based methods,our algorithm demonstrated ultrafast speed and higher accuracy,reduced sensitivity to defocusing,strong robustness and adaptability,making it an optimal choice for both two-dimensional and threedimensional super-resolution imaging analysis.
