The Imaging Server Kit is an initiative started by the EPFL Center for Imaging to develop a simple framework for creating and using interoperable image processing algorithms via a client/server system.
The kit includes:
- A collection of algorithms that can be deployed as web servers (with or without Docker) and run from QuPath or Napari, for a wide range of tasks:
Task | Examples | Napari | QuPath |
---|---|---|---|
Segmentation | StarDist, CellPose, Rembg, SAM-2, InstanSeg | ✅ | ✅ |
Object detection | Spotiflow, LoG detector | ✅ | ✅ |
Vector fields | Orientationpy | ✅ | ✅ |
Object tracking | Trackastra, Trackpy | ✅ | |
Image-to-Image | SPAM, Noise2Void | ✅ | |
Text-to-Image | Stable Diffusion | ✅ | |
Image-to-Text | Image captioning | ✅ | |
Classification | ResNet50 | ✅ |
- A Template to easily create new image processing algorithm servers.
The Imaging Server Kit is designed for:
- Algorithm developers: Test your tools in QuPath or Napari without having to create extensions or plugins.
- Non-technical Users: Use Python projects without needing to set them up on your computer.
- Server/Client: Run algorithms on a server that you connect to from client apps (Napari, QuPath).
- Auto-generated UI for algorithm parameters in QuPath and Napari. No need for separate extensions or plugins!
- Interoperable Algorithms that all accept inputs and express outputs in the same way.
- Dockerized: Build or pull a Docker image, then start/stop a container to use an algorithm.
March 2025
The Imaging Server Kit is under construction! Here is what we're up to:
- Make the
/info
route look nice - Screencast a tutorial on how to create a new algorithm server
- Add a server-side timeout to the
/process
endpoint - Improve the AuthenticatedServer
- Handle streaming/tiling for processing whole-slide images
- Add a sample image button in the QuPath extension
- QuPath extension can send annotations as algo inputs
- Make a Fiji plugin
- Mallory Wittwer, EPFL Center for Imaging (mallory.wittwer@epfl.ch)
- Edward Andò, EPFL Center for Imaging
- Maud Barthélémy, EPFL Center for Imaging
- Florian Aymanns, EPFL Center for Imaging
We acknowledge the Personalized Health and Related Technologies (PHRT) initiative for supporting this project.