DetecDiv, a deep-learning platform for automated cell division tracking and replicative lifespan analysis

Théo Aspert , Didier Hentsch , Gilles Charvin (1)

1 IGBMC - Institut de Génétique et de Biologie Moléculaire et Cellulaire

Abstract Automating the extraction of meaningful temporal information from sequences of microscopy images represents a major challenge to characterize dynamical biological processes. Here, we have developed DetecDiv, a microfluidic-based image acquisition platform combined with deep learning-based software for high-throughput single-cell division tracking. DetecDiv can reconstruct cellular replicative lifespans with an outstanding accuracy and provides comprehensive temporal cellular metrics using timeseries classification and image semantic segmentation.

Domaines: Sciences du Vivant [q-bio]

Théo Aspert, Didier Hentsch, Gilles Charvin. DetecDiv, a deep-learning platform for automated cell division tracking and replicative lifespan analysis. 2021. ⟨hal-03451298⟩