Motion-guided sparse correction enables expert-quality point tracking across diverse microscopy regimes
Quick Take
RIPPLE (Refinement Interpolation Platform for Point Location Estimation) enhances microscopy tracking by allowing users to make sparse corrections, achieving expert-level accuracy while reducing manual clicks by 3 to 25 times across five datasets, including jellyfish and sperm tracking. This innovation bridges the gap between manual annotation and fully automated tracking, facilitating immediate biological quantification and future tracker adaptation.
Key Points
- RIPPLE proposes full trajectories based on user-defined starting points.
- Achieves manual annotation quality while significantly reducing user input.
- Tested on five challenging microscopy datasets, including Clytia hemisphaerica.
- Enables immediate quantification of biological dynamics for researchers.
- Facilitates the creation of gold-standard data for future automated trackers.
Article Content
From source RSS / original summaryarXiv:2605. 29220v1 Announce Type: new Abstract: Tracking the dynamics of non-canonical biological systems in microscopy videos remains a persistent challenge. Both classical and learning-based trackers depend on expert-reviewed data to be evaluated and adapted, yet exhaustive manual annotation rarely scales to the videos where these tools are needed most.
We developed RIPPLE (Refinement Interpolation Platform for Point Location Estimation), which recasts annotation as sparse correction: a user clicks a starting point, RIPPLE proposes a full trajectory, and the user intervenes only where the trajectory drifts. We tested RIPPLE on five challenging microscopy datasets from our laboratories, four from the transparent jellyfish Clytia hemisphaerica and one tracking landmarks on rapidly moving sperm.
Across these, RIPPLE matched the quality of exhaustive manual annotation while reducing manual clicks by 3 to 25 times across datasets. RIPPLE thereby fills a missing layer between manual annotation and fully automated tracking, enabling immediate quantification of biological dynamics, method benchmarking, and the production of the gold-standard data needed to adapt future automated microscopy trackers.
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