NanoJ: a high-performance open-source super-resolution microscopy toolbox.
Romain F LaineKalina L ToshevaNils GustafssonRobert D M GrayPedro AlmadaDavid AlbrechtGabriel T RisaFredrik HurtigAnn-Christin LindåsBuzz BaumJason MercerChristophe LeterrierPedro Matos PereiraSiân CulleyRicardo HenriquesPublished in: Journal of physics D: Applied physics (2019)
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: 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.
Keyphrases
- data analysis
- high resolution
- single molecule
- label free
- high speed
- deep learning
- electronic health record
- optical coherence tomography
- atomic force microscopy
- mass spectrometry
- high throughput
- oxidative stress
- living cells
- palliative care
- quantum dots
- health information
- quality improvement
- machine learning
- healthcare
- case control
- fluorescent probe
- photodynamic therapy