Quantitative mapping and minimization of super-resolution optical imaging artifacts


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


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.

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