CHOTA: A Higher Order Accuracy Metric for Cell Tracking
Timo Kaiser, Vladimir Ulman, Bodo Rosenhahn

TL;DR
The paper introduces CHOTA, a new cell tracking evaluation metric that assesses global coherence and lineage accuracy, addressing limitations of existing metrics and improving biological relevance in cell tracking analysis.
Contribution
We propose CHOTA, a comprehensive cell tracking metric that unifies detection, association, coherence, and lineage evaluation, enhancing biological insight.
Findings
CHOTA is sensitive to all tracking errors.
It provides a better indication of lineage reconstruction quality.
It outperforms existing metrics in biological relevance.
Abstract
The evaluation of cell tracking results steers the development of tracking methods, significantly impacting biomedical research. This is quantitatively achieved by means of evaluation metrics. Unfortunately, current metrics favor local correctness and weakly reward global coherence, impeding high-level biological analysis. To also foster global coherence, we propose the CHOTA metric (Cell-specific Higher Order Tracking Accuracy) which unifies the evaluation of all relevant aspects of cell tracking: cell detections and local associations, global coherence, and lineage tracking. We achieve this by introducing a new definition of the term 'trajectory' that includes the entire cell lineage and by including this into the well-established HOTA metric from general multiple object tracking. Furthermore, we provide a detailed survey of contemporary cell tracking metrics to compare our novel…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsCell Image Analysis Techniques · Image Processing Techniques and Applications
