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    Drift correction for single-molecule imaging by molecular constraint field, a distance minimum metric.
    • Authors:
    • Renmin Han
      China; University of Chinese Academy of Sciences
      Liansan Wang
      Beijing Institute of Technology
      Beijing | China
      Fan Xu
      Suzhou University
      YongDeng Zhang
      Huazhong University of Science and Technology
      Mingshu Zhang
      National Laboratory of Biomacromolecules
      Zhiyong Liu
      St. Jude Children's Research Hospital
      United States
      Fei Ren
      Nanfang Hospital
      Fa Zhang
      Key Lab of Intelligent Information Processing and Advanced Computing Research Lab
    BMC Biophys 2015 13;8(1). Epub 2015 Jan 13.
    Key Lab of Intelligent Information Processing and Advanced Computing Research Lab, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190 China.
    Background: The recent developments of far-field optical microscopy (single molecule imaging techniques) have overcome the diffraction barrier of light and improve image resolution by a factor of ten compared with conventional light microscopy. These techniques utilize the stochastic switching of probe molecules to overcome the diffraction limit and determine the precise localizations of molecules, which often requires a long image acquisition time. However, long acquisition times increase the risk of sample drift. In the case of high resolution microscopy, sample drift would decrease the image resolution.

    Results: In this paper, we propose a novel metric based on the distance between molecules to solve the drift correction. The proposed metric directly uses the position information of molecules to estimate the frame drift. We also designed an algorithm to implement the metric for the general application of drift correction. There are two advantages of our method: First, because our method does not require space binning of positions of molecules but directly operates on the positions, it is more natural for single molecule imaging techniques. Second, our method can estimate drift with a small number of positions in each temporal bin, which may extend its potential application.

    Conclusions: The effectiveness of our method has been demonstrated by both simulated data and experiments on single molecular images.

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