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Napari plugin for analysing and visualizing lattice lightsheet and Oblique Plane Microscopy data. The plugin is optimized for data from the Zeiss lattice lightsheet microscope.

Project description

napari-lattice

License PyPI Python Version tests codecov napari hub

This napari plugin allows deskewing, cropping, visualisation and designing custom analysis pipelines for lattice lightsheet data, particularly from the Zeiss Lattice Lightsheet. Support will eventually be for other types of data.

Documentation

Check the Wiki page for documentation on how to get started.


LLSZ_overview

Functions

  • Deskewing and deconvolution of Zeiss lattice lightsheet images
    • Ability to preview deskewed image at channel or timepoint of interest
  • Crop and process only a small portion of the image
  • Import ImageJ ROIs for cropping
  • Create image processing workflows using napari-workflows
  • Run deskewing, deconvolution and custom image processing workflows from the terminal
  • Files can be saved as h5 (BigDataViewer/BigStitcher) or tiff files

Key Features

Apply custom image processing workflows using napari-workflows.

Support will be added for ome-zarr files in the future.


This napari plugin was generated with Cookiecutter using @napari's cookiecutter-napari-plugin template.

Contributing

Contributions are very welcome. Tests can be run with tox, please ensure the coverage at least stays the same before you submit a pull request.

License

======= Distributed under the terms of the [GPL-3.0 License] license, "napari_lattice" is free and open source software

Acknowledgment

This project was supported by funding from the Rogers Lab at the Centre for Dynamic Imaging at the Walter and Eliza Hall Institute of Medical Research. This project has been made possible in part by Napari plugin accelerator grant from the Chan Zuckerberg Initiative DAF, an advised fund of the Silicon Valley Community Foundation.

Thanks to the developers and maintainers of the amazing open-source plugins such as pyclesperanto, aicsimageio, dask and pycudadecon. ALso, thanks to the imagesc forum!

Issues

If you encounter any problems, please file an issue along with a detailed description.

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