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.

PMID: 31042738
PMCID: PMC6493727
Funding: - National Institute of Biomedical Imaging and Bioengineering: R03EB02935 - Division of Chemical, Bioengineering, Environmental, and Transport Systems: 1509713

Documentation

Links