Skip to Main content Skip to Navigation
Journal articles

Quantitative mapping and minimization of super-resolution optical imaging artifacts

Abstract : Super-resolution microscopy depends on steps that can contribute to the formation of image artifacts, leading to misinterpretation of biological information. We present NanoJ-SQUIRREL, an ImageJ-based analytical approach that provides quantitative assessment of super-resolution image quality. By comparing diffraction-limited images and super-resolution equivalents of the same acquisition volume, this approach generates a quantitative map of super-resolution defects and can guide researchers in optimizing imaging parameters.
Complete list of metadatas

Cited literature [6 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01736919
Contributor : Christophe Leterrier <>
Submitted on : Friday, April 20, 2018 - 4:20:19 PM
Last modification on : Thursday, November 7, 2019 - 10:46:01 AM
Long-term archiving on: : Tuesday, September 18, 2018 - 9:33:57 PM

File

2018_Nat. Methods_Culley.pdf
Explicit agreement for this submission

Identifiers

Collections

Citation

Siân Culley, David Albrecht, Caron Jacobs, Pedro Matos Pereira, Christophe Leterrier, et al.. Quantitative mapping and minimization of super-resolution optical imaging artifacts. Nature Methods, Nature Publishing Group, 2018, 15 (4), pp.263-266. ⟨10.1038/nmeth.4605⟩. ⟨hal-01736919⟩

Share

Metrics

Record views

220

Files downloads

875