Volume 4 Issue 8
Aug.  2013
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Yongdeng Zhang, Lusheng Gu, Hao Chang, Wei Ji, Yan Chen, Mingshu Zhang, Lu Yang, Bei Liu, Liangyi Chen, Tao Xu. Ultrafast, accurate, and robust localization of anisotropic dipoles[J]. Protein&Cell, 2013, 4(8): 598-606. doi: 10.1007/s13238-013-3904-1
Citation: Yongdeng Zhang, Lusheng Gu, Hao Chang, Wei Ji, Yan Chen, Mingshu Zhang, Lu Yang, Bei Liu, Liangyi Chen, Tao Xu. Ultrafast, accurate, and robust localization of anisotropic dipoles[J]. Protein&Cell, 2013, 4(8): 598-606. doi: 10.1007/s13238-013-3904-1

Ultrafast, accurate, and robust localization of anisotropic dipoles

doi: 10.1007/s13238-013-3904-1
Funds:

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), 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).

  • Received Date: 2013-04-26
  • Rev Recd Date: 2013-05-04
  • 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 artificial neural network for estimating the localization, orientation and mobility of individual dipoles. Compared with fitting-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.
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      沈阳化工大学材料科学与工程学院 沈阳 110142

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