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Updated: Sep 16, 2025

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Real-time super-resolution structured illumination microscopy: current progress in joint space and frequency

Tianyu Zhao1, Jingxiang Zhang1, Mengrui Wang1

  • 1Xi'an Jiaotong University, No.28 Xianning West Road, Xi'an, 710049, CHINA.

Reports on Progress in Physics. Physical Society (Great Britain)
|July 7, 2025
PubMed
Summary

Structured illumination microscopy (SIM) enables high-speed, super-resolution live cell imaging. A new joint space and frequency reconstruction (JSFR) framework achieves real-time image processing, overcoming current limitations.

Keywords:
real-time imagingstructured illumination microscopysuper-resolution microscopy

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Area of Science:

  • Biophysics
  • Cell Biology
  • Microscopy

Background:

  • Structured illumination microscopy (SIM) offers low light dose, high speed, and super-resolution for studying dynamic intracellular structures in living cells.
  • Current SIM reconstruction algorithms face challenges in achieving real-time imaging due to complex processing steps.
  • Improving reconstruction is crucial for "what you see is what you get" live cell imaging.

Purpose of the Study:

  • To review and compare existing super-resolution image reconstruction algorithms for SIM.
  • To propose a novel framework for real-time SIM image reconstruction.
  • To demonstrate the capability of the proposed framework in artifact reduction and real-time imaging.

Main Methods:

  • Comparative review of spatial frequency domain conversion, iterative parameter estimation, and deconvolution algorithms for SIM.
  • Development and implementation of a joint space and frequency reconstruction (JSFR) framework.
  • Application of the JSFR framework to 2D-SIM, 3D-SIM, and nonlinear SIM for real-time imaging.

Main Results:

  • The JSFR framework significantly enhances image reconstruction speed.
  • Real-time artifact reduction is achieved across various SIM modalities (2D, 3D, nonlinear).
  • The proposed technique demonstrates potential for live cell observation and deep learning applications.

Conclusions:

  • The JSFR framework represents a significant advancement for real-time SIM imaging.
  • This approach overcomes limitations of existing reconstruction algorithms, enabling faster and clearer live cell studies.
  • Future prospects include its use as a data platform for deep learning and advanced live cell microscopy.