Table C.9.

Key characteristics of all submitted algorithms. The winning team names are in bold. Colored circles in Awards represent first (gold), second (silver) and third (bronze) prizes a team has won in the challenge. Abbreviations: false positive (FP), extraction of brain mask (brain extract), resolution (res), binary (bin) or multiclass (mul) segmentation (seg), localization and extraction of custom ROI (ROI crop), Cross-Entropy (CE), intersection over union (IoU), centerline-boundary Dice (cb-Dice), binary topological interaction (BTI), skeleton recall (SkelRecall), region growing (grow).

Team	Awards	Input requiring paired modalities	Training using both modalities	Additional data used	3D data used	Data augmentation	CoW ROI used	# Stages	Multi-stage	Architectures	Loss function	Ensemble	Topological components
2i_mtl					✓	✓	provided	2	seg + reduce FP	AttentionUNet; Autoencoder	Dice + focal; MSE
agaldran					✓	✓		1		DynUNet	CE	✓
EURECOM			✓				provided	2	brain extract + seg	SynthSeg; A2V	Dice + CE
gbCoW					✓			1		nnUNet	Dice + CE	✓
gl					✓	✓	custom	3	ROI crop + bin seg + mul seg	MedNexT/UX-Net	Dice + CE	✓
IWantToGoToCanada					✓	✓		2	bin seg + mul seg	nnUNet; Swin-UNETR	Dice + CE; Dice + Focal	✓
junqiangchen					✓	✓	custom	2	ROI crop + seg	VNet3D	Dice + CE
lWM					✓	✓		1		ResUNet	Dice + Focal
NexToU					✓	✓		2	low-res bin seg + full-res seg	nnUNet; NexToU	Dice + CE + cb-Dice + BTI	✓	cb-Dice, BTI
NIC-VICOROB-1					✓	✓		1 – 2	bin seg + mul seg	nnUNet	Dice + CE	✓
NIC-VICOROB-2							provided	1 – 2	bin seg + mul seg	AttentionUNet	Focal
Organizers			✓		✓	✓	custom	2	ROI crop + seg	nnDetection; nnUNet	CE + IoU; Dice + CE	✓
refrain					✓	✓	custom	2	ROI crop + seg	nnUNet	Dice
sjtu_eiee_2-426lab					✓	✓	custom	2	ROI crop + seg	nnUNet	Dice + CE
UB-VTL					✓		provided	1		Brave-Net	clDice		clDice
UW					✓	✓		1		nnUNet	Dice + CE + TopK	✓
WilliWillsWissen			✓		✓	✓		1		nnUNet	Dice + CE + clDice + SkelRecall	✓	clDice, skeleton recall
ysato					✓			2	threshold + grow