Optimal 2D-SIM reconstruction by two filtering steps with Richardson-Lucy deconvolution

Victor Perez, Bo Jui Chang, Ernst Hans Karl Stelzer

Research output: Contribution to journalArticlepeer-review

44 Scopus citations


Structured illumination microscopy relies on reconstruction algorithms to yield super-resolution images. Artifacts can arise in the reconstruction and affect the image quality. Current reconstruction methods involve a parametrized apodization function and a Wiener filter. Empirically tuning the parameters in these functions can minimize artifacts, but such an approach is subjective and produces volatile results. We present a robust and objective method that yields optimal results by two straightforward filtering steps with Richardson-Lucy-based deconvolutions. We provide a resource to identify artifacts in 2D-SIM images by analyzing two main reasons for artifacts, out-of-focus background and a fluctuating reconstruction spectrum. We show how the filtering steps improve images of test specimens, microtubules, yeast and mammalian cells.

Original languageEnglish (US)
Article number37149
JournalScientific reports
StatePublished - Nov 16 2016
Externally publishedYes

ASJC Scopus subject areas

  • General


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