AI Article Synopsis
- - STED microscopy is a technique for super-resolution imaging of subcellular structures.
- - The paper discusses how deep learning restoration of STED images can significantly reduce photobleaching and photodamage by shortening pixel dwell time.
- - This new method enhances the quality and stability of noisy 2D and 3D STED images, which is particularly useful for studying mitochondrial dynamics over extended periods.
Article Abstract
STED microscopy is widely used to image subcellular structures with super-resolution. Here, we report that restoring STED images with deep learning can mitigate photobleaching and photodamage by reducing the pixel dwell time by one or two orders of magnitude. Our method allows for efficient and robust restoration of noisy 2D and 3D STED images with multiple targets and facilitates long-term imaging of mitochondrial dynamics.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10300082 | PMC |
| http://dx.doi.org/10.1038/s42003-023-05054-z | DOI Listing |
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