{"ID":6267124,"CreatedAt":"2026-07-10T01:11:38.759438437Z","UpdatedAt":"2026-07-13T01:02:08.706470581Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2607.08297","arxiv_id":"2607.08297","title":"ARGUS: Accelerated, Robust, General, and Unsupervised Cell Tracking Solutions","abstract":"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 fragments across short temporal gaps. Results: On publicly available Cell Tracking Challenge datasets, ARGUS achieved detection accuracy of 0.905-0.971 and tracking accuracy of 0.897-0.964, with runtimes within 1 minute (5-6 seconds for 3 frames). Conclusions: ARGUS is a modular, interpretable framework that can be adapted to different imaging modalities and biological applications without training data or GPU infrastructure. The implementation is publicly available at https://github.com/Gitinc/argus","short_abstract":"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, ove...","url_abs":"https://arxiv.org/abs/2607.08297","url_pdf":"https://arxiv.org/pdf/2607.08297v1","authors":"[\"Noah Jaitner\",\"Kandice Tanner\",\"Ingolf Sack\",\"Hossein S. Aghamiry\"]","published":"2026-07-09T09:40:38Z","proceeding":"cs.CV","tasks":"[\"cs.CV\",\"math.OC\"]","methods":"[]","has_code":false,"code_links":[{"ID":614079,"CreatedAt":"2026-07-10T01:11:38.759438437Z","UpdatedAt":"2026-07-10T01:11:38.759438437Z","DeletedAt":null,"paper_id":6267124,"paper_url":"https://arxiv.org/abs/2607.08297","paper_title":"ARGUS: Accelerated, Robust, General, and Unsupervised Cell Tracking Solutions","repo_url":"https://github.com/Gitinc/argus","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}