4.6 Article

High-precision 3D drift correction with differential phase contrast images

期刊

OPTICS EXPRESS
卷 29, 期 21, 页码 34641-34655

出版社

OPTICAL SOC AMER
DOI: 10.1364/OE.438160

关键词

-

类别

资金

  1. Hainan University [KYQD(ZR)-20077]
  2. China Postdoctoral Science Foundation [2020M682418]
  3. Fundamental Research Funds for the Central Universities [2018KFYXKJC039]
  4. National Natural Science Foundation of China [81827901]

向作者/读者索取更多资源

Single molecule localization microscopy often suffers from sample drift due to long image acquisition time, but using DPC microscopy can improve image contrast and provide a more precise and robust 3D drift correction method.
Single molecule localization microscopy (SMLM) usually requires long image acquisition time at the order of minutes and thus suffers from sample drift, which deteriorates image quality. A drift estimation method with high precision is typically used in SMLM, which can be further combined with a drift compensation device to enable active microscope stabilization. Among all the reported methods, the drift estimation method based on bright-field image correlation requires no extra sample preparation or complicated modification to the imaging setup. However, the performance of this method is limited by the contrast of bright-field images, especially for the structures without sufficient features. In this paper, we proposed to use differential phase contrast (DPC) microscopy to enhance the image contrast and presented a 3D drift correction method with higher precision and robustness. This DPC-based drift correction method is suitable even for biological samples without clear morphological features. We demonstrated that this method can achieve a correction precision of < 6 nm in both the lateral direction and axial direction. Using SMLM imaging of microtubules, we verified that this method provides a comparable drift estimation performance as redundant cross-correlation. (C) 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据