NanoJ: a high-performance open-source super-resolution microscopy toolbox
Romain F. Laine,
Kalina L. Tosheva,
Robert D. M. Gray,
Gabriel T. Risa,
Pedro M. Pereira,
Posted 01 Oct 2018
bioRxiv DOI: 10.1101/432674 (published DOI: 10.1088/1361-6463/ab0261)
Posted 01 Oct 2018
Super-resolution microscopy 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 super-resolution microscopy 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: spatio-temporal 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.
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