A sliding-window data aggregation method for super-resolution imaging of live cells

Kuan Chieh Jackie Chen, Yiyi Yu, Jelena Kovacevic, Ge Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Super resolution localization microscopy (SRLM) techniques such as STORM and PALM overcome the ∼200nm diffraction limit of conventional light microscopy by randomly activating separate fluorophores over time and computationally aggregating their nanometer resolution detected locations for image reconstruction. However, a basic limitation of current SRLM approaches for live cell imaging is their low temporal resolution due to motion blur, which arises if image objects move during image acquisition of the substantial number of raw images required for constructing the super-resolution image for a given time point. To overcome this limitation, we propose a sliding-window data aggregation method, which exploits the temporal correlation between the collected fluorescence images to achieve significantly higher frame rate and therefore better temporal resolution than current approaches. Specifically, images within a sliding window are aligned so that locations of detected fluorophores within them are aggregated to accelerate image reconstruction for higher temporal resolution. We tested and validated our method using both simulated and real live cell STORM image data.

Original languageEnglish (US)
Title of host publication2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015
PublisherIEEE Computer Society
Pages785-788
Number of pages4
ISBN (Electronic)9781479923748
DOIs
StatePublished - Jul 21 2015
Event12th IEEE International Symposium on Biomedical Imaging, ISBI 2015 - Brooklyn, United States
Duration: Apr 16 2015Apr 19 2015

Publication series

NameProceedings - International Symposium on Biomedical Imaging
Volume2015-July
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Other

Other12th IEEE International Symposium on Biomedical Imaging, ISBI 2015
CountryUnited States
CityBrooklyn
Period4/16/154/19/15

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Keywords

  • STORM
  • Super-resolution microscopy
  • fluorescence imaging
  • live cell imaging

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

Cite this

Chen, K. C. J., Yu, Y., Kovacevic, J., & Yang, G. (2015). A sliding-window data aggregation method for super-resolution imaging of live cells. In 2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015 (pp. 785-788). [7163989] (Proceedings - International Symposium on Biomedical Imaging; Vol. 2015-July). IEEE Computer Society. https://doi.org/10.1109/ISBI.2015.7163989