ArticleNature methods2025
Ultrack: pushing the limits of cell tracking across biological scales.
Article in Nature methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- Single-cell transcriptional dynamics in a living vertebrate.Cell systems · 2026Article
- Identifying phenotype-genotype-function coupling in 3D organoid imaging using Shape, Appearance and Motion Phenotype Observation Tool (SPOT).Nature communications · 2026Article
- Single-cell morphodynamics predict cell fate decisions during mucociliary epithelial differentiation.Molecular systems biology · 2026Article
- Bridging annotated microscopy imaging data and analysis method development for scientific discovery.Patterns (New York, N.Y.) · 2026Review
- Lights up on the embryonic dance: tools and applications of optogenetics in developmental biology.Genes & development · 2026Review
- Progress and new challenges in image-based profiling.Molecular systems biology · 2026Review
- High-throughput, organ-scale 3D tubule tracking using TubuleMAP.Research square · 2026Article
- High-throughput, organ-scale 3D tubule tracking using TubuleMAP.bioRxiv : the preprint server for biology · 2026Article
- Positional information and information flows in dynamic tissues.bioRxiv : the preprint server for biology · 2026Article
- Article
- Macrophages self-generate and refine chemotactic gradients during migration towards complement C5a.PLoS biology · 2026Article
- EpiCure (Epithelial Curation): a versatile and handy tool for curation of epithelial segmentation.bioRxiv : the preprint server for biology · 2026Article
- High-Fidelity Long-term Whole-embryo Lineage and Fate Reconstruction by Iterative Tracking with Error Correction.bioRxiv : the preprint server for biology · 2026Article
- An automated image analysis pipeline for wide-field optical redox imaging of patient-derived cancer organoids.Scientific reports · 2026Article
- A framework for evaluating predicted sperm trajectories in crowded microscopy videos.PLoS computational biology · 2026Article
- Distinct p21 dynamics drive alternative routes to whole-genome duplication through a common CDK4/6-dependent polyploid G0 state.bioRxiv : the preprint server for biology · 2026Article
- Visualizing the multidimensional landscape of biological variation in modern microscopy.Frontiers in bioinformatics · 2026Article
- Tui: A Multigenerational and Expert-Correctable Tracker for Cellular Dynamics.Computational and structural biotechnology journal · 2026Article
- Bayesian Transformers and Higher-Order Graph Matching for Cell Tracking in Serial Tissue Sections.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2026Article
- Advancing in vitro cell migration studies: a review of open-source analytical platforms for cancer and wound healing research.Cell adhesion & migration · 2025Review
Corrections and comments
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Authors and funding
16 authors.
Funding
Abstract
Tracking live cells across two-dimensional, three-dimensional (3D) and multichannel time-lapse recordings is crucial for understanding tissue-scale biological processes. Despite advancements in imaging technology, accurately tracking cells remains challenging, particularly in complex and crowded tissues where cell segmentation is often ambiguous. We present Ultrack, a versatile and scalable cell tracking method that tackles this challenge by considering candidate segmentations derived from multiple algorithms and parameter sets. Ultrack leverages temporal consistency to select optimal segments, ensuring robust performance even under segmentation uncertainty. We validate our method on diverse datasets, including terabyte-scale developmental time-lapse recordings of zebrafish, fruit fly and nematode embryos, as well as multicolor and label-free cellular imaging. We demonstrate that Ultrack achieves superior or comparable performance in the cell tracking challenge, particularly when tracking densely packed 3D embryonic cells over extended periods. Moreover, we propose an approach to tracking validation via dual-channel sparse labeling that enables high-fidelity ground-truth generation, pushing the boundaries of long-term cell tracking assessment. Our method is freely available as a Python package with Fiji and Napari plugins and can be deployed in a high-performance computing environment, facilitating widespread adoption by the research community.
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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 Socratic graph.