SQUIRREL is an analytical approach for quantifying image quality in super-resolution microscopy, provided as a GPU-enabled open-source ImageJ plugin. SQUIRREL requires two input images - a super-resolution image (or image stack) and the diffraction-limited equivalent of the same imaging volume. It then calculates an error-map, highlighting areas of the super-resolution image which exhibit poor agreement with the diffraction-limited image, and quality metrics for the super-resolution image.

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NanoJ: a high-performance open-source super-resolution microscopy toolbox
*Romain F Laine*, *Kalina L Tosheva*, *Nils Gustafsson*, *Robert DM Gray*, *Pedro Almada*, *David Albrecht*, Gabriel T Risa, Fredrik Hurtig, Ann-Christin Lindås, Buzz Baum, Jason Mercer, Christophe Leterrier, *Pedro M Pereira*, *Siân Culley*, *Ricardo Henriques*
Published in Journal of Physics D: Applied Physics, February 2019 (see publication)
Research themes: New Methods, Software
Type: Paper, Corresponding author
Content-aware image restoration: pushing the limits of fluorescence microscopy
Martin Weigert, Uwe Schmidt, Tobias Boothe, Andreas Müller, Alexandr Dibrov, Akanksha Jain, Benjamin Wilhelm, Deborah Schmidt, Coleman Broaddus, *Siân Culley*, Mauricio Rocha-Martins, Fabián Segovia-Miranda, Caren Norden, *Ricardo Henriques*, Marino Zerial, Michele Solimena, Jochen Rink, Pavel Tomancak, Loic Royer, Florian Jug, Eugene W Myers
Published in Nature methods, December 2018 (see publication)
Research themes: New Methods, Software
Type: Paper