FluoroCellTrack
FluoroCellTrack analyzes high-throughput droplet microfluidic bright-field and fluorescence microscopy images to detect droplets and cells, quantify encapsulation, and produce quantitative measures of cellular responses and intracellular fluorescence.
Key Features:
- Comprehensive data import: Imports images from bright-field and fluorescence microscopy for analysis of cellular dynamics within individual droplets.
- Implementation: Implemented in Python and operates independently of specific hardware platforms to handle diverse datasets from fluorescence detection systems.
- Dual detection mechanism: Employs Circular Hough Transform (CHT) for droplet detection and edge detection, dilation, erosion, segmentation, and thresholding based on radius and area for cell/contour identification.
- Overlay for encapsulation information: Overlays center maps of detected droplets and contours to determine encapsulation relationships between droplets and detected objects.
- Accuracy and performance: Demonstrates similarity to manual analysis with average accuracy of approximately 92–99% and reduces cohort analysis time to about 30 minutes versus ~20 hours manually.
- Droplet tracking: Provides capability to monitor and track individual droplets over time for dynamic analyses.
Scientific Applications:
- Quantification of cellular response to drugs: Enables measurement and analysis of cellular reactions to pharmacological agents within isolated droplets.
- Droplet tracking: Facilitates temporal monitoring of individual droplets to study dynamic processes.
- Intracellular fluorescence analysis: Supports detailed examination of intracellular fluorescence signals for studies of intracellular dynamics.
Methodology:
Images are imported and preprocessed; droplet detection uses Circular Hough Transform (CHT); cell/contour identification uses edge detection, dilation, erosion, segmentation, and thresholding with radius and area criteria; detected features are overlaid (center maps) and integrated for encapsulation analysis.
Topics
Details
- License:
- Unlicense
- Maturity:
- Mature
- Cost:
- Free of charge
- Tool Type:
- command-line tool
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- Python
- Added:
- 8/9/2019
- Last Updated:
- 6/16/2020
Operations
Publications
Vaithiyanathan M, Safa N, Melvin AT. FluoroCellTrack: An algorithm for automated analysis of high-throughput droplet microfluidic data. PLOS ONE. 2019;14(5):e0215337. doi:10.1371/journal.pone.0215337. PMID:31042738. PMCID:PMC6493727.