Abstract
Super-resolution microscopy surpasses the diffraction limit to enable the observation of the fine details in sub-cellular structures and their dynamics in diverse biological processes within living cells. Structured illumination microscopy (SIM) uses a relatively low illumination light power compared with other super-resolution microscopies and has great potential to meet the demands of live-cell imaging. However, the imaging acquisition and reconstruction speeds limit its further applications. In this article, recent developments all targeted at improving the overall speed of SIM are reviewed. These comprise both hardware and software improvements, which include a reduction in the number of raw images, GPU acceleration, deep learning and the spatial domain reconstruction. We also discuss the application of these developments in live-cell imaging.
| Original language | English (US) |
|---|---|
| Article number | 672555 |
| Journal | Frontiers in Physics |
| Volume | 9 |
| DOIs | |
| State | Published - May 28 2021 |
Keywords
- SIM
- fluorescence microscopy
- hardware acceleration of deep learning
- image reconstructed algorithm
- super-resolution
ASJC Scopus subject areas
- Biophysics
- Materials Science (miscellaneous)
- Mathematical Physics
- General Physics and Astronomy
- Physical and Theoretical Chemistry