Results - WMH Segmentation Challenge

The table below presents the up-to-date results of the WMH Segmentation Challenge. Methods are ranked according to the five evaluation criteria.

#	Team	Rank	DSC	H95 (mm)	AVD (%)	Recall	F1
1	pgs	0.0185	0.81	5.63	18.58	0.82	0.79
2	sysu_media_2	0.0187	0.80	5.76	28.73	0.87	0.76
3	sysu_media	0.0288	0.80	6.30	21.88	0.84	0.76
4	buckeye_ai	0.0314	0.79	6.17	22.99	0.83	0.77
5	tum_ibbm	0.0318	0.79	5.90	22.33	0.83	0.76
6	pitt-vamp-2	0.0385	0.79	5.74	19.69	0.81	0.76
7	coroflo	0.0493	0.79	5.46	22.53	0.76	0.77
8	neuro.ml_2	0.0511	0.78	6.33	30.63	0.82	0.73
9	cian	0.0571	0.78	6.82	21.72	0.83	0.70
10	bioengineering_espol_team	0.0596	0.78	6.24	28.26	0.78	0.74
11	nlp_logix	0.0678	0.77	7.16	18.37	0.73	0.78
12	pitt-vamp	0.0753	0.79	8.85	19.53	0.76	0.73
13	nih_cidi_2	0.0803	0.75	7.35	27.26	0.81	0.69
14	bigrbrain_2	0.0847	0.77	9.46	28.04	0.78	0.71
15	uned_stand_2021	0.0866	0.79	6.37	17.56	0.69	0.73
16	fmrib-truenet_2	0.0891	0.77	6.95	20.49	0.74	0.70
17	bigrbrain	0.0910	0.78	6.75	23.24	0.70	0.73
18	uned_2	0.0927	0.78	7.59	27.69	0.77	0.66
19	nic-vicorob	0.0927	0.77	8.28	28.54	0.75	0.71
20	rasha_improved	0.0964	0.77	7.42	24.97	0.76	0.67
21	wta	0.1012	0.78	6.78	16.20	0.66	0.73
22	dice	0.1046	0.77	7.63	19.77	0.69	0.71
23	uned_enhanced_2021	0.1063	0.79	7.23	18.64	0.66	0.71
24	fmrib-truenet	0.1114	0.75	8.91	27.93	0.72	0.70
25	wta_2	0.1132	0.76	8.21	21.31	0.67	0.72
26	misp_2	0.1178	0.78	11.10	19.71	0.68	0.71
27	acunet_2-2	0.1346	0.71	8.34	22.58	0.69	0.70
28	uned_contrast	0.1355	0.75	9.90	44.33	0.77	0.60
29	k2	0.1531	0.77	9.79	19.08	0.59	0.70
30	uned	0.1552	0.73	11.04	55.84	0.81	0.54
31	rasha_simple	0.1562	0.74	9.05	29.73	0.65	0.64
32	acunet_2-4	0.1642	0.69	10.30	26.14	0.63	0.71
33	acunet_2-1	0.1696	0.69	8.96	28.99	0.65	0.65
34	acunet	0.1735	0.65	9.22	29.35	0.67	0.67
35	lrde	0.1797	0.73	14.54	21.71	0.63	0.67
36	misp	0.1821	0.72	14.88	21.36	0.63	0.68
37	acunet_2-3	0.2033	0.66	10.31	28.40	0.58	0.67
38	ipmi-bern	0.2625	0.69	9.72	19.92	0.44	0.57
39	nih_cidi	0.2843	0.68	12.82	196.38	0.59	0.54
40	arg	0.2879	0.70	21.54	46.11	0.53	0.57
41	scan	0.2898	0.63	14.34	34.67	0.55	0.51
42	tig_corr	0.3039	0.68	17.48	39.07	0.54	0.46
43	livia	0.3044	0.61	22.70	38.39	0.54	0.61
44	achilles	0.3081	0.63	11.82	24.41	0.45	0.52
45	caai_amh	0.3090	0.62	15.03	28.54	0.45	0.57
46	skkumedneuro	0.3604	0.58	19.02	58.54	0.47	0.51
47	tignet	0.3909	0.59	21.58	86.22	0.46	0.45
48	tig	0.3955	0.60	17.86	34.34	0.38	0.42
49	knight	0.4239	0.70	17.03	39.99	0.25	0.35
50	upc_dlmi	0.4449	0.53	27.01	208.49	0.57	0.42
51	himinn	0.4500	0.62	24.49	44.19	0.33	0.36
52	nist	0.4830	0.53	15.91	109.98	0.37	0.25
53	text_class	0.5781	0.50	28.23	146.64	0.27	0.29
54	neuro.ml	0.6074	0.51	37.36	614.05	0.71	0.21
55	hadi	0.8940	0.23	52.02	828.61	0.58	0.11

Results presented at MICCAI 2017 in Quebec City can be found here: MICCAI results.