The acia library provides utility functionality for analyzing 2D+t time-lapse image sequences in microfluidic live-cell imaging experiments.
Project description
Acia: Automated single-cell image analysis
Accio 🪄 - and your single-cell insights appear - Not quite but - acia - and your single-cell insights appear to become much easier 😉
The acia library provides a modular image analysis pipeline utility functionality for analysing 2D+t time-lapse image sequences in microfluidic live-cell imaging experiments. It provides:
- Abstraction for various image sources (local, OMERO)
- automated image analysis for instance segmentation and tracking (eight SOTA AI approaches supported out of the box)
- automated and unit-aware single-object property extraction.
- extended visualization in videos, charts and interactive charts including segmentation masks and lineage trees
Although the funtionality is developed with microfluidic applications in mind, the library can be used for any objects detected in images.
Note: For examples of its usage please visit our application workflow collection including more than 10 real-world examples: https://github.com/JuBiotech/acia-workflows
Installation
Install acia from pypi:
pip install acia
Developers
- Clone this repository
git clone https://github.com/JuBiotech/acia-core.git cd acia-core
2.Install acia in development mode
```bash
pip install -e .
```
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