Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Live cell image segmentation

K Wu1, D Gauthier, M D Levine

  • 1Center for Intelligent Machines, McGill University, Montreal, Quebec, Canada.

IEEE Transactions on Bio-Medical Engineering
|January 1, 1995
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Inter-laboratory variability in cytomegalovirus DNA quantification: implications for standardization and clinical monitoring.

Journal of clinical microbiology·2025
Same author

Protective effects of Saccharomyces boulardii CNCM I-745 in an experimental model of NSAID-induced enteropathy.

Beneficial microbes·2023
Same author

Characterisation of microbunching instability with 2D Fourier analysis.

Scientific reports·2020
Same author

Control of H_{2} Dissociative Ionization in the Nonlinear Regime Using Vacuum Ultraviolet Free-Electron Laser Pulses.

Physical review letters·2018
Same author

Coherent THz Emission Enhanced by Coherent Synchrotron Radiation Wakefield.

Scientific reports·2018
Same author

Experimental induction of mouthrot in Atlantic salmon smolts using Tenacibaculum maritimum from Western Canada.

Journal of fish diseases·2018
Same journal

Enhancing Volumetric Imaging in Linear-Array Photoacoustic Tomography: multiview fusion with deep learning.

IEEE transactions on bio-medical engineering·2026
Same journal

Robust Rule-based Heuristic Assistance Strategy for a Semi-Active Shoulder Exoskeleton Used in Overhead Work.

IEEE transactions on bio-medical engineering·2026
Same journal

Highly Accelerated 1-mm Isotropic 3D Chemical Exchange Saturation Transfer MRI Using Wave-Co-CAIPI at 5 Tesla.

IEEE transactions on bio-medical engineering·2026
Same journal

Systematic Evaluation of Hip Exoskeleton Assistance Parameters for Enhancing Gait Stability During Ground Slip Perturbations.

IEEE transactions on bio-medical engineering·2026
Same journal

SleepConFormer: A Single-Channel EEG Framework for Sleep Staging and Consciousness Assessment in Patients with Disorders of Consciousness.

IEEE transactions on bio-medical engineering·2026
Same journal

Modeling Partial and Total Support of Left Ventricular Assist Device for Discrete Hemodynamic Control Framework.

IEEE transactions on bio-medical engineering·2026
See all related articles

This study introduces a fast and robust two-stage method for segmenting live cell images, improving automated cell tracking systems by overcoming challenges with low-contrast and unevenly illuminated images.

Area of Science:

  • Computer Vision
  • Biomedical Imaging
  • Cell Biology

Background:

  • Automated, real-time, computer vision-based cell tracking systems require efficient cell image segmentation.
  • Existing segmentation algorithms perform poorly on live, unstained cell images due to low contrast, intensity variation, and uneven illumination.

Purpose of the Study:

  • To develop a robust and efficient cell image segmentation strategy for automated cell tracking.
  • To address the limitations of current methods in handling challenging live cell image characteristics.

Main Methods:

  • A two-stage segmentation strategy is proposed.
  • Stage 1: Extract an approximate region of the cell and surrounding background.
  • Stage 2: Segment the cell within the extracted region to minimize background influence.

Related Experiment Videos

Main Results:

  • The proposed method effectively reduces the impact of background intensity and texture on cell region extraction.
  • Experimental results demonstrate the approach is both fast and robust for cell image segmentation.
  • Achieved improved segmentation accuracy for challenging live unstained cell images.

Conclusions:

  • The developed two-stage segmentation strategy offers a significant improvement for automated cell tracking systems.
  • This method provides a fast and robust solution for segmenting difficult live cell images.
  • Enhances the reliability and efficiency of computer vision applications in cell biology.