This website contains a dataset designed for low-frame-rate cell tracking. While deep learning has improved tracking accuracy, most methods rely on high-frame-rate imaging, which can cause photobleaching and phototoxicity. Low-frame-rate imaging minimizes these effects but presents additional challenges for automated tracking algorithms.
Our dataset includes long-term image sequences (1–2 days) at varying magnifications, with ground-truth annotations for cell identification, mitosis, and movement. This resource wants to support research on more robust tracking solutions for large-scale biological studies.