NanoJ: A high-performance open-source super-resolution microscopy toolbox

Romain F. Laine, Kalina L. Tosheva, Nils Gustafsson, Robert D.M. 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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

29 Citations (Scopus)
144 Downloads (Pure)

Abstract

Super-resolution microscopy (SRM) has become essential for the study of nanoscale biological processes. This type of imaging often requires the use of specialised image analysis tools to process a large volume of recorded data and extract quantitative information. In recent years, our team has built an open-source image analysis framework for SRM designed to combine high performance and ease of use. We named it NanoJ - a reference to the popular ImageJ software it was developed for. In this paper, we highlight the current capabilities of NanoJ for several essential processing steps: spatiooral alignment of raw data (NanoJ-Core), super-resolution image reconstruction (NanoJ-SRRF), image quality assessment (NanoJ-SQUIRREL), structural modelling (NanoJ-VirusMapper) and control of the sample environment (NanoJ-Fluidics). We expect to expand NanoJ in the future through the development of new tools designed to improve quantitative data analysis and measure the reliability of fluorescent microscopy studies.

Original languageEnglish
Article number163001
JournalJournal of Physics D: Applied Physics
Volume52
Issue number16
Early online date28 Jan 2019
DOIs
Publication statusPublished - 18 Feb 2019

Keywords

  • Fiji
  • fluidics
  • image analysis
  • image quality assessment
  • ImageJ
  • single-particle analysis
  • Super-resolution microscopy

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Acoustics and Ultrasonics
  • Surfaces, Coatings and Films

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