Segment organoids in brightfield from nd2 stack
This napari plugin was generated with Cookiecutter using @napari's cookiecutter-napari-plugin template.
pip install git+https://github.com/aaristov/napari-segment.git
- Drag your nd2 file into napari
- Lauch Plugins -> napari-segment: Segment prognoid
- Select the brightfield channel
- The data is lazily loaded from nd2 dataset and dynamically segmented in the viewer.
- Theshold and erode parameters allow you to adjust segmentation -> they all will appear in the Detections layer
- Min/max diameter and eccentricity allow you to filter out unwanted regions -> the good regions will appear in the "selected labels" layer.
- You can deactivate the Detection layer with a checkbox.
- Once saticfied, simply save the selected labels layer with build-in napari saver for future use and downstream analysis.
- Drag and drop the folder with mutiscale zarr dataset.
- The plugin will look for the napari attributes in the .zattr file and render the stack accordingly. See the example below for 4D dataset:
{
"multiscales": {
"multiscales": [
{
"channel_axis": 1,
"colormap": [
"gray",
"green",
"blue"
],
"datasets": [
{
"path": "0"
},
{
"path": "1"
},
{
"path": "2"
},
{
"path": "3"
}
],
"lut": [
[
1000,
30000
],
[
440,
600
],
[
0,
501
]
],
"name": [
"BF",
"TRITC",
"mask"
],
"title": "BF_TRITC_aligned.zarr",
"type": "nd2",
"version": "0.1"
}
]
}
}
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-segment" is free and open source software
If you encounter any problems, please file an issue along with a detailed description.