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Spotiflow: napari plugin

Napari plugin for Spotiflow, a deep learning-based, threshold-agnostic, and subpixel-accurate spot detection method for 2D and 3D fluorescence microscopy images. The plugin allows using several pre-trained models as well as user-trained ones. For the main repository, see here.

https://github.com/weigertlab/napari-spotiflow/assets/11042162/02940480-daa9-4a21-8cf5-ad73c26c9838

If you use this plugin for your research, please cite us as well as napari.

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Installation

The plugin can be installed directly from PyPi (make sure you use a conda environment with napari and spotiflow installed):

pip install napari-spotiflow

Usage

1. Open the image (or open one of our samples, e.g. File > Open Sample > napari-spotiflow > HybISS)
2. Start the plugin Plugins > napari-spotiflow
3. Select model (pre-trained or custom trained) and optionally adjust any other parameters
4. Click Detect spots

Supported input formats

• 2D (YX, YXC or CYX)
• 2D+t (TYX, TYXC or TCYX)
• 3D (ZYX, ZYXC or CZYX)
• 3D+t (TZYX, TZYXC or TCZYX)

How to cite

See the main repository's How to cite section as well as napari's citing napari section.