ARGUS: Accelerated, Robust, General, and Unsupervised Cell Tracking Solutions
Background and Objective: Quantitative analysis of cell dynamics is central to modern biological research, providing critical insights into immune cell interactions, disease progression, and drug mechanisms. Automated cell tracking in time-lapse microscopy remains challenging due to noise, morphological variations, overlapping cells, and dynamic events such as divisions and fusions. Methods: We present ARGUS, a framework for Accelerated, Robust, General, and Unsupervised Cell Tracking Solutions. ARGUS combines adaptive cell detection, dense Farneback optical-flow prediction, frame-to-frame linear assignment, and a sequence-level tracklet-refinement step that reconnects trajectory fragment...
| Authors | Noah Jaitner, Kandice Tanner, Ingolf Sack et al. |
|---|---|
| Primary category | cs.CV |
| Published | 9 July 2026 |
| Last updated at source | 9 July 2026 |
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