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Optical Sectioning and High Resolution in Single-Slice Structured Illumination Microscopy by Thick Slice Blind-SIM
Aurélie Jost1, Elen Tolstik1, Polina Feldmann1
1Institute of Physical Chemistry, Abbe Center of Photonics, Friedrich-Schiller University Jena, Jena, Germany; Leibniz-Institute of Photonic Technology, Jena, Germany.
Structured Illumination Microscopy (SIM) can now create clear images from thick fluorescent samples using a single focal plane. This new thick slice blind-SIM method overcomes out-of-focus light and improves resolution.
Area of Science:
- Microscopy
- Optical Imaging
- Biophysics
Background:
- Microscopy of thick fluorescent samples suffers from out-of-focus light and limited resolution.
- Standard imaging techniques struggle to achieve optical sectioning and high transverse resolution simultaneously.
Purpose of the Study:
- To develop a novel method for reconstructing high-resolution, tightly sectioned images from single focal planes of thick fluorescent samples.
- To adapt existing blind-SIM techniques to handle complex illumination patterns and sample-induced distortions.
Main Methods:
- Utilized a single 2D focal plane dataset from Structured Illumination Microscopy (SIM).
- Adapted a blind-SIM reconstruction algorithm capable of handling unknown and distorted illumination patterns.
- Developed a novel algorithm, termed 'thick slice blind-SIM', which models a 3D sample from 2D data.
Main Results:
- Achieved images with significantly improved optical sectioning compared to conventional methods.
- Demonstrated high transverse resolution, effectively overcoming diffraction limits.
- The algorithm successfully compensated for illumination distortions caused by the sample and optics.
Conclusions:
- Single-plane SIM data can be computationally processed to yield high-resolution, sectioned images of thick samples.
- The thick slice blind-SIM algorithm offers a robust solution for challenging imaging scenarios in fluorescence microscopy.
- This technique enhances imaging capabilities for thick biological specimens without requiring complex 3D data acquisition.
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