Ultrack: pushing the limits of cell tracking across biological scales

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 3, 2024

Tracking live cells across 2D, 3D, and multi-channel time-lapse recordings is crucial for understanding tissue-scale biological processes. Despite advancements in imaging technology, achieving accurate cell tracking remains challenging, particularly complex crowded tissues where segmentation often ambiguous. We present Ultrack, a versatile scalable cell-tracking method that tackles this challenge by considering candidate segmentations derived from multiple algorithms parameter sets. Ultrack employs temporal consistency to select optimal segments, ensuring robust performance even under uncertainty. validate our on diverse datasets, including terabyte-scale developmental time-lapses of zebrafish, fruit fly, nematode embryos, as well multi-color label-free cellular imaging. show achieves state-of-the-art the Cell Challenge demonstrates superior accuracy densely packed embryonic over extended periods. Moreover, we propose an approach validation via dual-channel sparse labeling enables high-fidelity ground truth generation, pushing boundaries long-term assessment. Our freely available Python package with Fiji napari plugins can be deployed high-performance computing environment, facilitating widespread adoption research community.

Language: Английский

A comprehensive update on the application of high-throughput fluorescence imaging for novel drug discovery

Expert Opinion on Drug Discovery, Journal Year: 2025, Volume and Issue: unknown

Published: April 30, 2025

Language: Английский

In silico labeling in cell biology: Potential and limitations

Current Opinion in Cell Biology, Journal Year: 2024, Volume and Issue: 89, P. 102378 - 102378

Published: June 4, 2024

Language: Английский