Explore image in channel coordinate space.
Brainbow dataset have unique features that need to be addressed by specialized tools. This plugin aims at visualize and diagnose brainbow dataset.
In particular we want to interact with the distribution in the channel space. This plugin allows you to visualize the distribution of the channel ratio in the image and to select pixel in the image and see where they are in the channel coordinate space. You can also use this plugin along with the napari-cluster-plotter
plugin plugin to visualize the distribution of the channel ratio of every point object in the image.
The following channel spaces are available:
- Cartesian RGB
- Hue-Saturation-Value planes illustration (b)(f)
- Hue-Saturation wheel illustration (g)
- Maxwell triangle (ternary plot) illustration
- Spherical coordinates (Theta, Phi and Radius) illustration
You can use this plugin to visualize channel space of !
- every voxel in the image (see demo notebook)
- every object (aka center point) in the image (see demo notebook). To use this notebook you need to install
napari-cluster-plotter
plugin. Find all menus underPlugins > napari-brainbow-diagnose > Diagnose Brainbow Image
If you want to use your dataset, you have to format it such as each channel is in one distinct napari.Layers
You can open test dataset to try this plugin in File > Open Sample > napari-brainbow-diagnose
.
- The RGB Cube is an array with shape (3x256x256x256) cube : Great to check how the plugin work when all color are represented
- ChroMS Cortex Sample is an array with shape (3x256x256x256) #Hugo : Real life brainbow image (Cortex E18 Emx1Cre) !
Once you have your layers you can use the dropdown and select the corresponding layer. It is advised to match the red, green, blue
order so the ratio you see on the napari viewer corresponds to the Hue-Saturation Wheel of the plugin.
When you click on Compute brainbow image density
you will populate the Hue-Saturation density Wheel.
This should allow you to quickly see which ratio is more present in your image. You can see the corresponding ratio according to the "HS Color wheel" on the right.
For example here on this screenshot we can see that:
- there is a high number of non saturated red-only ratio. (2)
- there is not a high number of non saturated magenta ratio. (3)
You can install napari-brainbow-diagnose
via pip:
pip install napari-brainbow-diagnose
To install latest development version :
pip install git+https://github.com/LaboratoryOpticsBiosciences/napari-brainbow-diagnose.git
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.
Distributed under the terms of the BSD-3 license, "napari-brainbow-diagnose" is free and open source software
If you encounter any problems, please file an issue along with a detailed description.
This napari plugin was generated with Cookiecutter using @napari's cookiecutter-napari-plugin template.