Example dataset for Tracking Metrics using TrackMate and Oneat
<p>In this dataset we compare the automated tracking results using the standard TrackMate algorithms for frame to frame and segment to segment linking with the ground truth dataset. Furthermore we use Oneat to correct the branches of the lineage trees and using oneat as TrackCorrector we recompute the metrics to show improvements over TrackMate track linking algorithms.</p> <p>Tracking Metrics</p> <p>Simple LAP tracker + Oneat</p> <p>{DET : 0.9964, CT : 0.73531, TRA : 0.9933, TF : 0.97518, BCi : 0.10526}</p> <p>LAP Tracker with track splitting and Quality as additional cost</p> <p>{DET : 0.9900, CT : 0.677033, TRA : 0.986785; TF : 0.95041, BCi : 0.04347}</p> <p>LAP Tracker with track splitting and Quality as additional cost + Oneat</p> <p>{DET : 0.98911, CT : 0.672629, TRA : 0.985774, TF : 0.948692, BCi : 0.05555}</p> <p>LAP Tracker without track splitting and Quality as additional cost + Oneat</p> <p>{DET : 0.990083, CT : 0.6766, TRA : 0.986742, TF : 0.9521, BCi 0.054}</p>
ShareScore
36/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 0