Assessment¶

There is only 1 track for the multiclass segmentation task, for both CT and MR modalities.

Metrics for TopBrain Vessel Segmentation¶

Seven categories of evaluation metrics, in total 12 metrics with equal weights, for the whole brain anatomical vessel segmentation task:

1. Class-average Dice similarity coefficient
2. Class-average centerline Dice (clDice)
3. Class-average error on number of connected components
4. Class-average Hausdorff distance 95% percentile (HD95)
5. Class-average error on number of invalid neighbors
   • Each vessel has a list of valid neighbor vessels
   • Neighborhood is defined by adjacency or "touching"
6. Average F1 score (harmonic mean of the precision and recall) for detection of the "side road" vessels
   • "Highway" vs "side road" vessels
   • List of side-road vessels is documented in the constants.py in our evaluation code and in the preprint. See below.
7. Contamination metrics (six metrics)
   • Class-average foreground contamination (FGC) ratio
   • Class-average number of FGC sources
   • Class-average undersegmentation (UnderSeg) ratio
   • Class-average number of undersegmented classes
   • Number of background contamination (BGC) voxels
   • Number of BGC sources

Evaluation Code¶

Whatever we use for the challenge evaluation will be released and synchronized to the following repo in a transparent manner. Please refer to this repo for our assessment implementations.

Please feel free to leave an issue or let us know if you have further feedback or questions.

Further Readings¶

• Yang K, Shi P, Huang H, Musio F, Baazaoui H, Aydin OU, Hilbert A, Hamadache RE, Yalcin C, Zhang M, Falcetta D. TopBrain segmentation challenge for whole brain vessel anatomy. medRxiv. 2026 May 30:2026-05. (Preprint link)