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  1. Home
  3. A Dynamic Contour Evolution Algorithm For Cell Segmentation And Synaptic Tracking Under Occlusion.
  1. Home
  3. A Dynamic Contour Evolution Algorithm For Cell Segmentation And Synaptic Tracking Under Occlusion.

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Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules
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A Dynamic Contour Evolution Algorithm for Cell Segmentation and Synaptic Tracking under Occlusion.

Chen-Xi Zhang1, Xin-Gui Yu2, Ming-Kang Li3

  • 1School of Pharmacy, Nanjing Medical University, Nanjing 211166, P. R. China.

Chemical & Biomedical Imaging
|June 1, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

We developed a new algorithm combining contour deformation networks and graph neural networks to accurately track single cells, even with challenging cell shapes and overlaps. This tool quantifies cellular dynamics and reveals how oxidative stress impacts cell migration.

Keywords:
Cell migrationCell morphologyCell segmentationCell trackingDynamic contour evolutionFT-KAN

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Area of Science:

  • Cell biology
  • Bioinformatics
  • Computational biology

Background:

  • Cell migration is crucial for biological processes but challenging to quantify due to cell variability and occlusion.
  • Dysregulation of cell migration is linked to various diseases.

Purpose of the Study:

  • To develop a robust algorithm for accurate single-cell segmentation and tracking.
  • To enable precise quantification of cellular dynamics under diverse conditions.

Main Methods:

  • A novel framework combining Dynamic Profile Evolution (DPE) contour deformation network and a graph neural network (GNN).
  • Algorithm designed to handle morphological variability and cell occlusion for reliable tracking.
  • Validation on HT22 cell datasets demonstrating improved recognition and identity continuity.

Main Results:

  • The DPE-GNN framework accurately segments and tracks cells, outperforming existing methods.
  • Analysis of over 4,000 cells revealed stable morphology and migration patterns under normal conditions.
  • Oxidative stress was observed to reduce cell motility and alter migration trajectories.

Conclusions:

  • The developed framework provides a versatile tool for precise quantification of cellular dynamics.
  • Enables long-term live-cell monitoring and high-content analysis of cell behaviors.
  • Offers insights into how environmental factors like oxidative stress affect cell migration patterns.