5 papers
DART: A design-aware microfluidic chip paradigm for real-time live-cell image analysis
Johannes Seiffarth, Matthias Pesch, Lukas Scholtes +3
High-throughput microfluidic live-cell imaging generates rich single-cell data. Yet semi-automated procedures for locating regions of interest (RoIs), each containing one cell popu…
PyUAT: Open-source Python framework for efficient and scalable cell tracking
Johannes Seiffarth, Katharina Nöh
Tracking individual cells in live-cell imaging provides fundamental insights, inevitable for studying causes and consequences of phenotypic heterogeneity, responses to changing env…
How To Make Your Cell Tracker Say "I dunno!"
Richard D. Paul, Johannes Seiffarth, David Rügamer +2
Cell tracking is a key computational task in live-cell microscopy, but fully automated analysis of high-throughput imaging requires reliable and, thus, uncertainty-aware data analy…
Tracking one-in-a-million: Large-scale benchmark for microbial single-cell tracking with experiment-aware robustness metrics
J. Seiffarth, L. Blöbaum, R. D. Paul +6
Tracking the development of living cells in live-cell time-lapses reveals crucial insights into single-cell behavior and presents tremendous potential for biomedical and biotechnol…
Robust Approximate Characterization of Single-Cell Heterogeneity in Microbial Growth
Richard D. Paul, Johannes Seiffarth, Hanno Scharr +1
Live-cell microscopy allows to go beyond measuring average features of cellular populations to observe, quantify and explain biological heterogeneity. Deep Learning-based instance…