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 Concept Videos

You might also read

Related Articles

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

Sort by
Same author

How do supermarkets shape the experience of vulnerable people in Australia's food system? A scoping review.

Nutrition & dietetics : the journal of the Dietitians Association of Australia·2026
Same author

Coordinated regulation of mRNA translation and stability by ZC3H7A and ZC3H7B RNA-binding proteins.

Cell reports·2026
Same author

Ultra-processed food supply in hospitals: A cross-sectional analysis of Australian hospitals using cook fresh foodservices.

Nutrition & dietetics : the journal of the Dietitians Association of Australia·2026
Same author

Direct Mapping of CDK2 Substrates in Embryonic Stem Cells Uncovers an AP-Site Repair Mechanism via HMCES Phosphorylation.

bioRxiv : the preprint server for biology·2026
Same author

Quantitative CDK2 Dynamics Are Linked to Cell Fate Decisions in Differentiating Trophoblast Stem Cells.

bioRxiv : the preprint server for biology·2026
Same author

Food waste measurement in Australian hospitals and residential aged care homes.

Frontiers in nutrition·2025

Related Experiment Video

Updated: Jul 24, 2025

Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules
00:10

Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules

Published on: September 5, 2019

8.3K

DeepSea is an efficient deep-learning model for single-cell segmentation and tracking in time-lapse microscopy.

Abolfazl Zargari1, Gerrald A Lodewijk2, Najmeh Mashhadi3

  • 1Department of Electrical and Computer Engineering, University of California, Santa Cruz, Santa Cruz, CA, USA.

Cell Reports Methods
|July 10, 2023
PubMed
Summary

DeepSea, a novel deep-learning model, precisely segments and tracks single cells in phase-contrast microscopy images. This advancement aids in analyzing cellular dynamics and heterogeneity, crucial for understanding fundamental biological processes.

Keywords:
Cell biologycell segmentationcell sizecell trackingdeep learninglive imagingmicroscopy

More Related Videos

Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture
09:04

Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture

Published on: February 23, 2018

9.5K
AMEBaS: Automatic Midline Extraction and Background Subtraction of Ratiometric Fluorescence Time-Lapses of Polarized Single Cells
06:03

AMEBaS: Automatic Midline Extraction and Background Subtraction of Ratiometric Fluorescence Time-Lapses of Polarized Single Cells

Published on: June 23, 2023

502

Related Experiment Videos

Last Updated: Jul 24, 2025

Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules
00:10

Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules

Published on: September 5, 2019

8.3K
Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture
09:04

Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture

Published on: February 23, 2018

9.5K
AMEBaS: Automatic Midline Extraction and Background Subtraction of Ratiometric Fluorescence Time-Lapses of Polarized Single Cells
06:03

AMEBaS: Automatic Midline Extraction and Background Subtraction of Ratiometric Fluorescence Time-Lapses of Polarized Single Cells

Published on: June 23, 2023

502

Area of Science:

  • Cell Biology
  • Microscopy Techniques
  • Bioinformatics

Background:

  • Time-lapse microscopy offers high temporal resolution for observing cellular dynamics and heterogeneity at the single-cell level.
  • Automated cell segmentation and tracking are essential for analyzing large datasets from time-lapse microscopy.
  • Current methods struggle with accurate segmentation and tracking, especially using non-toxic phase-contrast imaging.

Purpose of the Study:

  • To develop a versatile and trainable deep-learning model for automated single-cell segmentation and tracking.
  • To improve the precision of cell tracking in phase-contrast live microscopy image sequences.
  • To demonstrate the model's utility in analyzing cell size regulation in embryonic stem cells.

Main Methods:

  • Development of DeepSea, a deep-learning model for simultaneous segmentation and tracking.
  • Training and validation of the model on phase-contrast live microscopy image sequences.
  • Application of DeepSea to analyze cell size regulation in embryonic stem cells.

Main Results:

  • DeepSea achieves higher precision in single-cell segmentation and tracking compared to existing models.
  • The model demonstrates robustness in handling phase-contrast microscopy images.
  • Successful analysis of cell size regulation dynamics using the DeepSea model.

Conclusions:

  • DeepSea provides a significant advancement in automated single-cell analysis for time-lapse microscopy.
  • The model enhances the capability to study cellular dynamics and heterogeneity using accessible imaging modalities.
  • DeepSea is a valuable tool for cell biology research, particularly in areas like cell size regulation.