Usiigaci
A semi-automated pipeline for instance-aware cell segmentation, tracking, and migration analysis in phase contrast microscopy using Mask R-CNN.
What is Usiigaci?
Usiigaci is an open-source software pipeline for automated cell tracking in phase contrast microscopy. It uses supervised machine learning (Mask R-CNN) to segment individual cells, track their movements over time, and analyze migration parameters like speed and directionality. It solves the problem of manually tracing cells in microscopy videos, which is time-consuming and error-prone.
Biologists and biomedical researchers studying cell migration, electrotaxis, or other dynamic cellular processes using phase contrast microscopy. It's also suitable for bioimage analysts needing automated, instance-aware segmentation tools.
Usiigaci provides high-accuracy, stain-free cell tracking with whole-cell morphology analysis, which is difficult even with fluorescent imaging. Its semi-automated pipeline reduces manual labor while offering robust performance across varying microscopy conditions.
Overview
Usiigaci: stain-free cell tracking in phase contrast microscopy enabled by supervised machine learning
Use Cases
Best For
- Quantifying cell migration parameters in wound healing assays
Related Projects
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
