The napari hub is transitioning to a community-run implementation due to launch in June 2025.
Since October 1, 2024, this version is no longer actively maintained and will not be updated. New plugins and plugin updates will continue to be listed.

napari-stitcher

napari-stitcher

Stitch napari image layers in 2-3D+t

This plugin stitches images (napari layers) in 2/3D+t. Images can either be (pre-)aligned manually or on a grid.

Here's it's user guide and github repository. napari-stitcher uses multiview-stitcher for registration and fusion.

Overview

Image data by Arthur Michaut @ Jérôme Gros Lab @ Institut Pasteur.

  1. Directly stitch napari layers: Use napari to load, visualize and preposition the tiles to be stitched.
  2. When working with multi-channel data, stick to the following naming convention: {tile} :: {channel}.
  3. Load either all or just a subset of the layers into the plugin.
  4. Choose registration options: registration channel, binning and more.
  5. Stitching = registration (refining the positions, optional) + fusion (joining the tiles into a single image).
  6. The registration result is shown in the viewer and the fused channels are added as new layers.

Demo

Link to video demo.

This demo uses the awesome napari-threedee for prepositioning the tiles. Image data: BigStitcher.

Version:

  • 0.1.0

Last updated:

  • 18 October 2024

First released:

  • 18 October 2024

License:

Supported data:

  • Information not submitted

Open extension:

Save extension:

Save layers:

GitHub activity:

  • Stars: 15
  • Forks: 4
  • Issues + PRs: 3

Python versions supported:

Operating system:

Requirements:

  • numpy>=1.18
  • magicgui
  • qtpy
  • tifffile>=2022.7.28
  • multiview-stitcher[aicsimageio]==0.1.14
  • spatial-image==0.3.0
  • multiscale-spatial-image==0.11.2