ArticleeLife2021
3DeeCellTracker, a deep learning-based pipeline for segmenting and tracking cells in 3D time lapse images.
Article in eLife, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.
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Who cites it
60 citing papers in PubMed.
- Review
- Celldetective, an AI-enhanced image analysis tool for unraveling dynamic cell interactions.eLife · 2026Article
- Single-cell morphodynamics predict cell fate decisions during mucociliary epithelial differentiation.Molecular systems biology · 2026Article
- Semi-automatic 3D-quantification of in-vivo synapse formation.BMC bioinformatics · 2026Article
- Lights up on the embryonic dance: tools and applications of optogenetics in developmental biology.Genes & development · 2026Review
- Ex vivo imaging reveals neutrophil behaviors in the adult zebrafish heart.Journal of cell science · 2026Article
- Localized heat induces ERK activation and signal propagation in solid tumors.Scientific reports · 2026Article
- Deep neural networks to register and annotate cells in moving and deforming nervous systems.eLife · 2026Article
- Artificial intelligence-powered microscopy: Transforming the landscape of parasitology.Journal of microscopy · 2026Review
- Methods to analyze cell migration data: fundamentals and practical guidelines.Nature methods · 2026Review
- Deep learning reveals how cells pull, buckle, and navigate fibrous environments.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Single-cell morphodynamics predict cell fate decisions during mucociliary epithelial differentiation.bioRxiv : the preprint server for biology · 2025Article
- Integrative functional optical imaging approaches: Optics, microfluidics, and machine learning for neuroscience in organoids and small-animal models.Biophysical journal · 2025Review
- Cell tracking with accurate error prediction.Nature methods · 2025Article
- 3DCellComposer - A versatile pipeline utilizing 2D cell segmentation methods for 3D cell segmentation.Methods (San Diego, Calif.) · 2025Article
- Volumetric imaging and computation to explore contractile function in zebrafish hearts.Cell reports methods · 2025Article
- AI-driven 3D bioprinting for regenerative medicine: From bench to bedside.Bioactive materials · 2025Review
- Exploring the Impact of Variability in Cell Segmentation and Tracking Approaches.Microscopy research and technique · 2025Article
- Article
- Unifying community whole-brain imaging datasets enables robust neuron identification and reveals determinants of neuron position in C. elegans.Cell reports methods · 2025Article
Corrections and comments
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Authors and funding
14 authors.
Funding
Abstract
Despite recent improvements in microscope technologies, segmenting and tracking cells in three-dimensional time-lapse images (3D + T images) to extract their dynamic positions and activities remains a considerable bottleneck in the field. We developed a deep learning-based software pipeline, 3DeeCellTracker, by integrating multiple existing and new techniques including deep learning for tracking. With only one volume of training data, one initial correction, and a few parameter changes, 3DeeCellTracker successfully segmented and tracked ~100 cells in both semi-immobilized and 'straightened' freely moving worm's brain, in a naturally beating zebrafish heart, and ~1000 cells in a 3D cultured tumor spheroid. While these datasets were imaged with highly divergent optical systems, our method tracked 90-100% of the cells in most cases, which is comparable or superior to previous results. These results suggest that 3DeeCellTracker could pave the way for revealing dynamic cell activities in image datasets that have been difficult to analyze.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.