Quantitative mapping and minimization of super-resolution optical imaging artifacts

Research output: Contribution to journalLetterpeer-review


  • Siân Culley
  • David Albrecht
  • Caron Jacobs
  • Pedro Matos Pereira
  • Christophe Leterrier
  • Ricardo Henriques

Colleges, School and Institutes

External organisations

  • UCL
  • The Francis Crick Institute
  • CNRS/Aix-Marseille Universite


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.


Original languageEnglish
Pages (from-to)263-266
Number of pages4
JournalNature Methods
Issue number4
Publication statusPublished - 3 Apr 2018