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An ultra-fast algorithm for high-density localization microscopy (Conference Presentation)
Author(s): Hongqiang Ma; Yang Liu

Paper Abstract

High-density localization of multiple fluorescent emitters is a common strategy to improve the temporal resolution of super-resolution localization microscopy. In recent years, various high-density localization algorithms have been developed. Despite their rigorous mathematical model and the subsequent improvement in image resolution, they still suffer from high computing complexity and the resulting extremely low computation speed, thus limiting the application to either small dataset or expensive computer clusters. It is still impractical as a routine tool for a large dataset. With the recent advance of high-throughput localization microscopy with sCMOS cameras that can produce a huge amount of data in a short period of time, fast processing now becomes even more important. Here, we present a simple algebraic algorithm based on our previously developed method, gradient fitting, for fast and precise high-density localization of multiple overlapping fluorescent emitters. Through numerical simulation and biological experiments, we showed that our algorithm can yield comparable localization precision and recall rate as DAOSTORM in various densities and signal levels, but with much simpler computation complexity. After being implemented on a GPU device (NVidia GTX1080) for parallel computing, it can run over three orders of magnitude faster than DAOSTORM implemented on a high-end workstation. Therefore, our method presents a possibility for online reconstruction of high-speed super-resolution imaging with high-density fluorescent emitters.

Paper Details

Date Published: 29 September 2017
PDF
Proc. SPIE 10350, Nanoimaging and Nanospectroscopy V, 103500G (29 September 2017); doi: 10.1117/12.2275789
Show Author Affiliations
Hongqiang Ma, Univ. of Pittsburgh (United States)
Yang Liu, Univ. of Pittsburgh (United States)


Published in SPIE Proceedings Vol. 10350:
Nanoimaging and Nanospectroscopy V
Prabhat Verma; Alexander Egner, Editor(s)

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