Hessian structured illumination microscopy (original) (raw)
- In Brief
- Published: 31 May 2018
MICROSCOPY
Nature Methods volume 15, page 407 (2018)Cite this article
- 3877 Accesses
- 5 Citations
- 2 Altmetric
- Metrics details
Subjects
Huang, X. et al. Nat. Biotechnol. 36, 451–459 (2018).
Structured illumination microscopy (SIM) offers twice the resolving power of diffraction-limited microscopy with relatively low doses of light compared with those required for other super-resolution modes, which makes it useful for live imaging. However, SIM involves image reconstruction that is prone to artifacts. Huang et al. have developed an approach called Hessian-SIM to reduce artifacts in SIM image reconstruction for improved fast live-cell super-resolution imaging. Hessian-SIM uses a deconvolution algorithm based on Hessian matrices that makes use of a priori knowledge of an imaged structure to guide image reconstruction. This deconvolution algorithm outperforms current algorithms at low signal intensities and allows imaging at a fraction of the photon dose of conventional SIM. Using their approach, the researchers carried out hour-long time-lapse imaging of actin filaments in live cells and were able to image never-before-observed structures involved in endocytosis.
Author information
Authors and Affiliations
- Nature Methods http://www.nature.com/nmeth
Rita Strack
Authors
- Rita Strack
You can also search for this author inPubMed Google Scholar
Corresponding author
Correspondence toRita Strack.
Rights and permissions
About this article
Cite this article
Strack, R. Hessian structured illumination microscopy.Nat Methods 15, 407 (2018). https://doi.org/10.1038/s41592-018-0023-1
- Published: 31 May 2018
- Issue Date: June 2018
- DOI: https://doi.org/10.1038/s41592-018-0023-1
This article is cited by
Democratising deep learning for microscopy with ZeroCostDL4Mic
- Lucas von Chamier
- Romain F. Laine
- Ricardo Henriques
Nature Communications (2021)