Cell tracking improved through machine learning

Abstract

The work is devoted to assessing the challenges and advancements in microscopy data analysis, focusing on cell tracking, object detection, lineage reconstruction, and the application of machine learning. It highlights the difficulties in accurate lineage reconstruction, the importance of metrics in assessing tracking algorithms, and the role of machine learning in proposing hypotheses and understanding complex biological systems.