Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

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

Contact Cluster Modeling of Allosteric Communication in PDZ Domains.

The journal of physical chemistry. B·2026

Same author

Robustness and innovation in synthetic genotype networks.

Nature communications·2023

Same author

pyPOCQuant - A tool to automatically quantify Point-Of-Care Tests from images.

SoftwareX·2022

Same author

Results from Canton Grisons of Switzerland suggest repetitive testing reduces SARS-CoV-2 incidence (February-March 2021).

Scientific reports·2022

Same author

Cell region fingerprints enable highly precise single-cell tracking and lineage reconstruction.

Nature methods·2022

Same author

High-resolution mass measurements of single budding yeast reveal linear growth segments.

Nature communications·2022

Same journal

3DICE: Interpretable 3D Cross-Modal Learning for Drug-Target Interaction Prediction and Large-Scale Drug Discovery.

Bioinformatics (Oxford, England)·2026

Same journal

KASSPer: Kinase Active Site Structure Prediction using Protein and Ligand Language Models and Its Application to Virtual Screening.

Bioinformatics (Oxford, England)·2026

Same journal

IDR searcher: a search engine solution for public image resources.

Bioinformatics (Oxford, England)·2026

Same journal

KCFtools: Rapid alignment-free method for introgression screening and GWAS using k-mer profiles.

Bioinformatics (Oxford, England)·2026

Same journal

Meta2DB: Curated shotgun metagenomic feature sets and metadata for health state prediction.

Bioinformatics (Oxford, England)·2026

Same journal

conMItion: an R package adjusting confounding factors for associations in multi-omics.

Bioinformatics (Oxford, England)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Apr 29, 2026

Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging

Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging

Published on: April 30, 2019

Accurate cell segmentation in microscopy images using membrane patterns.

Sotiris Dimopoulos¹, Christian E Mayer¹, Fabian Rudolf²

¹Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland, Swiss Institute of Bioinformatics, ETH Zurich, 4058 Basel, Switzerland Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland, Swiss Institute of Bioinformatics, ETH Zurich, 4058 Basel, Switzerland.

Bioinformatics (Oxford, England)

|May 23, 2014

Summary

This summary is machine-generated.

Accurate cell segmentation is crucial for microscopy. This new method uses cell membrane intensity profiles for improved boundary detection, outperforming existing techniques in various conditions.

More Related Videos

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

Automated Quantification of Hematopoietic Cell – Stromal Cell Interactions in Histological Images of Undecalcified Bone

Automated Quantification of Hematopoietic Cell – Stromal Cell Interactions in Histological Images of Undecalcified Bone

Published on: April 8, 2015

Related Experiment Videos

Last Updated: Apr 29, 2026

Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging

Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging

Published on: April 30, 2019

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

Automated Quantification of Hematopoietic Cell – Stromal Cell Interactions in Histological Images of Undecalcified Bone

Automated Quantification of Hematopoietic Cell – Stromal Cell Interactions in Histological Images of Undecalcified Bone

Published on: April 8, 2015

Area of Science:

Quantitative single-cell biology
Optical microscopy
Bioimage analysis

Background:

Cell segmentation is vital for quantitative single-cell biology using optical microscopy.
Existing segmentation methods often require problem-specific tuning and primarily use image gradient fields.
Cell membrane intensity profiles, common in microscopy, remain underexploited for general segmentation.

Purpose of the Study:

To develop an automatic cell segmentation method that leverages cell membrane intensity profiles.
To improve the accuracy and generalizability of cell boundary detection in microscopy images.

Main Methods:

Developed an automatic cell segmentation method utilizing graph cuts.
Incorporated directional cross-correlations to decode cell membrane information.
Integrated spatial constraints for robust boundary detection.

Main Results:

The method achieves optimal per-cell boundary detection by decoding cell membrane information.
Successfully segmented various cell types in dense cultures across different microscopy techniques.
Demonstrated significantly improved segmentation performance compared to established methods on synthetic and real images, handling cell shape irregularity, variability, and noise.

Conclusions:

The novel method offers a more general and accurate approach to cell segmentation.
Successfully applied the method to monitor protein internalization in yeast cells, showcasing its utility in biological studies.