@@ -10,9 +10,28 @@ Temporal registration of 2D/3D movies on one channel based on [itk-elastix](http
Adaptated from [multireg](https://gitlab.pasteur.fr/gletort/multireg) for temporal movies.
For a tutorial on using `elastix` for registration, see [this tutorial](https://m-albert.github.io/elastix_tutorial/intro.html).
*[Installation](#installation)
*[System requirement](#system-requirement)
*[Installation steps](#installation-steps)
*[Usage](#usage)
*[Demo](#demotest)
*[License](#license)
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## Installation
# Installation
## System requirement
`napari-3dtimereg` is a Napari plugin therefore can be installed on all operating systems.
It requires a python environement compatible with `Napari` and `elastix` version.
### Tested system
It has been tested on python 3.9, napari XX and elastix XX.
## Installation steps
In a python environment that contains Napari:
* You can install the plugin directly in `Napari` by going to `Plugins>Install/Uninstall plugins` and search for `napari-3dtimereg`
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@@ -21,7 +40,10 @@ For a tutorial on using `elastix` for registration, see [this tutorial](https://
pip install napari-3dtimereg
## Usage
If you don't have Napari installed yet, see [here](https://napari.org/stable/tutorials/fundamentals/quick_start.html#napari-quick-start) for installation instructions.
# Usage
You can launch `3dtimereg` in napari by going to `Plugins>Do 3D movie registration (napari-3dtimereg)`.
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@@ -58,9 +80,41 @@ When all frames have been processed, each color chanel and each frame have been
If you click on `Concatenate aligned images` on the plugin interface, the plugin will create a single composite movie from the aligned images, save it and delete the separated images in the `aligned` folder.
## License
Distributed under the terms of the [BSD-3] license, "napari-3dtimereg" is free and open source software
# Demo/Test
To test this plugin, you can use our [demo dataset](./data/demo_input) proposed in this repository or directly on your own dataset.
## Steps
The input of the process should be a `.tiff` 3D and temporal stack with one or more channels.
If you want to use fix points registration option, you should have a file that contains the position of each tracked point at each time.
See in our demo dataset for the format of this file.
It can be for example generated from a [TrackMate](https://imagej.net/plugins/trackmate/) file with the macro [getTrackPosition](XX) proposed in this repository.
Activate your python virtual environement in which napari and the plugin are installed.
For example, if the name of the environment is `timereg-env`, type: `conda activate timereg-env`.
When it's activated, type `napari` to start Napari.
Go to `Plugins>napari-3dtimereg` to start it.
The dialog interface appears to let you choose the folder to process (the one containing your data), the neural networks to use (that you can download from this repository [`FiberFromTransMatch.zip`](./networks/)) and the parameters to you want to use (see [options](#options) part for more details).
Press `Ok` to launch it. If you selected the `visible` mode, images will pop up during the process and you can visualize the different steps. Otherwise, you will only get informations of the plugin advancement in the `Log` window.
## Output
At the end of the process, you will get a folder named `aligned` in which all processed stacks will be saved (registered stacks) with the corresponding TrackMate files if you selected the option.
You can see what you can obtain with our [demo dataset](./data/demo_output).
**Running time**: On a standard computer with one GPU, running the plugin on one image take typically around XXX for a movie wit XX Z-slices and XX time frames.
# License
Distributed under the terms of the [BSD-3] license, "napari-3dtimereg" is free and open source software.
If you use it, please cite our paper [Sarde et al.](https://www.biorxiv.org/content/10.1101/2025.03.13.643016v1).
