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

FALCON: Closed-Loop Multi-Objective Optimization of Lipid Nanoparticles for Cell-Selective mRNA Delivery.

bioRxiv : the preprint server for biology·2026

Same author

IL-11 neutralizing antibodies alleviate pulmonary fibrosis in aging mice by inhibiting TGF-β/NOX4/IL-11 signaling pathway.

Biochemical pharmacology·2026

Same author

Automated Working Alliance Assessment in Psychological Counseling Using Gemini and XGBoost.

Entropy (Basel, Switzerland)·2026

Same author

CRISPR-Cas12a-based fluorescent and visual assays for universal detection and clade discrimination of mpox virus.

Microbiology spectrum·2026

Same author

CortexCAM: A Camera Array Microscope for Cortex-Wide Cellular Imaging in Freely Locomoting Mice.

Research square·2026

Same author

Lipid nanoparticle composition directs systemic trafficking and tissue-specific T cell immunity after intramuscular injection.

Nature biomedical engineering·2026

Same journal

Layered social competition coordinates reproductive hierarchy formation in ants.

bioRxiv : the preprint server for biology·2026

Same journal

Combination epigenetic-targeted therapy increases the immunogenicity of poorly immunogenic sarcomas.

bioRxiv : the preprint server for biology·2026

Same journal

Loss of LanC-like proteins delays post-injury regeneration of aging skeletal muscles.

bioRxiv : the preprint server for biology·2026

Same journal

Integrative Transfer Network: Deep Transfer Learning Across Populations and Prediction Targets.

bioRxiv : the preprint server for biology·2026

Same journal

Confidence-supported label-free metabolic imaging with FPhaS phase autofluorescence microscopy.

bioRxiv : the preprint server for biology·2026

Same journal

Sequence-encoded autoinhibition couples mRNA decapping activity to phase separation.

bioRxiv : the preprint server for biology·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 5, 2026

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Published on: November 7, 2025

Foundation cell segmentation models performance on live microscopy and spatial-omics data.

Yang Miao¹, Nick Surguladze², Josh Lerner¹

¹Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA.

Biorxiv : the Preprint Server for Biology

|May 4, 2026

Summary

This summary is machine-generated.

Choosing the right deep learning cell segmentation model is crucial for biological image analysis. Different models excel on specific imaging types, impacting downstream analyses like cell identification.

More Related Videos

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

Related Experiment Videos

Last Updated: May 5, 2026

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Published on: November 7, 2025

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

Area of Science:

Computational Biology
Bioimaging Analysis
Deep Learning Applications

Background:

Accurate cell segmentation is vital for quantitative biological imaging.
Deep learning models show promise across various imaging modalities.
Limited systematic comparisons exist for downstream biological analysis.

Purpose of the Study:

Evaluate recent deep learning cell segmentation models.
Compare model performance on phase contrast, fluorescence, and multiplexed tissue imaging.
Assess impact on downstream analyses like clustering and cell identification.

Main Methods:

Tested Cellpose cyto3, Cellpose-SAM, μSAM, CellSAM on phase contrast and fluorescence images.
Benchmarked Mesmer and InstanSeg on CO-Detection by IndEXing (CODEX) tissue images.
Analyzed downstream effects on clustering and cell type identification.

Main Results:

Cellpose-SAM performed well on phase contrast images.
SAM-based models showed strong results on fluorescence cell culture data.
No single model dominated CODEX datasets; performance varied by model strengths and limitations.

Conclusions:

Model selection for cell segmentation should align with dataset characteristics and analytical objectives.
A universal approach to cell segmentation is not optimal.
Understanding model-specific strengths is key for reliable biological insights.