TABLE II:

Segmentation results of LGE, BOLD and T2, when training with a varying amount of annotations for ERI, BOLD, and CHAOS datasets respectively.

ERI: Target LGE Dice (Source cine)
Method	50%	25%	12.5%
copy	6706	6706	6706
register	6807	6807	6807
AC	6615	6615	6615
UNet-single	7612	6614	5121
SDNet-single	7604	6909	5418
UNet-multi	7608	6711	5019
SDNet-multi	7604	7307	6419
DualStream	7603	6113	4423
Translation	7507	6714	6214
DADR	7705	6611	5719
DAFNet	${\mathbf{78}}_{04}^{\ast }$	${\mathbf{76}}_{05}^{\ast }$	${\mathbf{74}}_{05}^{\ast }$
BOLD: Target BOLD Dice (Source cine)
Method	50%	25%	12.5%
copy	8001	8001	8001
register	8104	8104	8104
AC	6802	6802	6802
UNet-single	7917	5927	4929
SDNet-single	8403	6817	6414
UNet-multi	8703	7517	7213
SDNet-multi	8607	8503	8003
DualStream	8601	5826	4928
Translation	8402	7906	4726
DADR	8702	7901	7115
DAFNet	8701	8603	${\mathbf{85}}_{03}^{\ast }$
CHAOS: Target T2 Dice (Source T1)
Method	50%	25%	12.5%
copy	7110	7110	7110
register	7007	7007	7007
AC	6522	6522	6522
UNet-single	8017	7615	7217
SDNet-single	8214	7716	7514
UNet-multi	8415	7916	7516
SDNet-multi	8411	8013	7809
DualStream	8119	7816	7516
Translation	8107	7511	7010
DADR	8411	7714	7411
DAFNet	8405	8203	${\mathbf{79}}_{05}^{\ast }$