CellTracker
CellTracker is open-source cell tracking software for quantitative analysis of cell migration and cell segmentation. It features machine learning algorithms for automated cell tracking and can analyze cell motility and morphology.
cell-tracking
cell-segmentation
cell-motility
open-source
CellTracker: Open-Source Cell Tracking Software
Quantitative analysis of cell migration and cell segmentation, featuring machine learning algorithms for automated cell tracking and analysis of cell motility and morphology.
What is CellTracker?
CellTracker is an open-source software tool for quantitative analysis of cell migration and segmentation of phase contrast microscopy images. It enables tracking of cell trajectories over time and extraction of motility parameters. CellTracker features machine learning based algorithms for automated cell tracking, eliminating the need for manual tracking.
Key features of CellTracker include:
- Automated tracking of cell centroids over time
- Characterization of cell migration modes - endothelial, amoeboid, mesenchymal
- Analysis of cell morphology dynamics
- Segmentation of cell boundaries
- Customizable algorithms and tracking parameters
- Support for modification and addition of new algorithms
- Extraction of over 100 migration and morphology parameters
- User-friendly graphical interface
- Compatible with Windows, Mac, and Linux systems
- Free and open-source software
CellTracker enables deep quantitative analysis of cell migratory behavior and morphology dynamics for applications in cell biology, immunology, cancer research, drug discovery, and regenerative medicine.
CellTracker Features
Features
- Automated cell tracking using machine learning algorithms
- Cell segmentation and quantitative analysis of cell morphology
- Analysis of cell motility and migration
- Open-source software with Python API
- Customizable workflows and analysis pipelines
- Support for time-lapse, multi-channel fluorescence and phase contrast microscopy images
- Cell tracking validation and manual error correction tools
- Quantitative measurements of cell speed, displacement, trajectory etc.
- Cell lineage reconstruction and cell fate mapping
- Segmentation of subcellular compartments
- Analysis of cell-cell interactions
Pricing
- Open Source
Pros
Automated and accurate cell tracking
In-depth quantitative analysis features
Free and open-source
Customizable and extensible
Support for different microscopy modalities
Active development community
Cons
Requires programming skills for full utilization
Limited user interface compared to commercial software
Steep learning curve
Lacks some specialized analysis tools
Official Links
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