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	0.0215	0.81	5.63	18.58	0.82	0.79
2	sysu_media_2	0.0220	0.80	5.76	28.73	0.87	0.76
3	sysu_media	0.0320	0.80	6.30	21.88	0.84	0.76
4	buckeye_ai	0.0345	0.79	6.17	22.99	0.83	0.77
5	tum_ibbm	0.0349	0.79	5.90	22.33	0.83	0.76
6	pitt-vamp-2	0.0415	0.79	5.74	19.69	0.81	0.76
7	coroflo	0.0520	0.79	5.46	22.53	0.76	0.77
8	neuro.ml_2	0.0541	0.78	6.33	30.63	0.82	0.73
9	nus_mnndl	0.0568	0.76	6.92	50.28	0.88	0.71
10	cian	0.0602	0.78	6.82	21.72	0.83	0.70
11	bioengineering_espol_team	0.0625	0.78	6.24	28.26	0.78	0.74
12	nlp_logix	0.0704	0.77	7.16	18.37	0.73	0.78
13	pitt-vamp	0.0780	0.79	8.85	19.53	0.76	0.73
14	nih_cidi_2	0.0833	0.75	7.35	27.26	0.81	0.69
15	bigrbrain_2	0.0876	0.77	9.46	28.04	0.78	0.71
16	uned_stand_2021	0.0890	0.79	6.37	17.56	0.69	0.73
17	fmrib-truenet_2	0.0917	0.77	6.95	20.49	0.74	0.70
18	bigrbrain	0.0934	0.78	6.75	23.24	0.70	0.73
19	nic-vicorob	0.0954	0.77	8.28	28.54	0.75	0.71
20	uned_2	0.0954	0.78	7.59	27.69	0.77	0.66
21	rasha_improved	0.0991	0.77	7.42	24.97	0.76	0.67
22	wta	0.1033	0.78	6.78	16.20	0.66	0.73
23	dice	0.1070	0.77	7.63	19.77	0.69	0.71
24	uned_enhanced_2021	0.1085	0.79	7.23	18.64	0.66	0.71
25	fmrib-truenet	0.1139	0.75	8.91	27.93	0.72	0.70
26	wta_2	0.1154	0.76	8.21	21.31	0.67	0.72
27	misp_2	0.1201	0.78	11.10	19.71	0.68	0.71
28	uned_enhanced_2022	0.1215	0.75	6.79	17.68	0.66	0.71
29	acunet_2-2	0.1369	0.71	8.34	22.58	0.69	0.70
30	uned_contrast	0.1383	0.75	9.90	44.33	0.77	0.60
31	k2	0.1549	0.77	9.79	19.08	0.59	0.70
32	uned	0.1581	0.73	11.04	55.84	0.81	0.54
33	rasha_simple	0.1584	0.74	9.05	29.73	0.65	0.64
34	acunet_2-4	0.1662	0.69	10.30	26.14	0.63	0.71
35	acunet_2-1	0.1718	0.69	8.96	28.99	0.65	0.65
36	acunet	0.1758	0.65	9.22	29.35	0.67	0.67
37	lrde	0.1818	0.73	14.54	21.71	0.63	0.67
38	misp	0.1842	0.72	14.88	21.36	0.63	0.68
39	acunet_2-3	0.2051	0.66	10.31	28.40	0.58	0.67
40	ipmi-bern	0.2635	0.69	9.72	19.92	0.44	0.57
41	nih_cidi	0.2862	0.68	12.82	196.38	0.59	0.54
42	arg	0.2894	0.70	21.54	46.11	0.53	0.57
43	scan	0.2914	0.63	14.34	34.67	0.55	0.51
44	tig_corr	0.3055	0.68	17.48	39.07	0.54	0.46
45	livia	0.3060	0.61	22.70	38.39	0.54	0.61
46	achilles	0.3092	0.63	11.82	24.41	0.45	0.52
47	caai_amh	0.3101	0.62	15.03	28.54	0.45	0.57
48	skkumedneuro	0.3616	0.58	19.02	58.54	0.47	0.51
49	tignet	0.3921	0.59	21.58	86.22	0.46	0.45
50	tig	0.3963	0.60	17.86	34.34	0.38	0.42
51	knight	0.4239	0.70	17.03	39.99	0.25	0.35
52	upc_dlmi	0.4466	0.53	27.01	208.49	0.57	0.42
53	himinn	0.4505	0.62	24.49	44.19	0.33	0.36
54	nist	0.4836	0.53	15.91	109.98	0.37	0.25
55	text_class	0.5782	0.50	28.23	146.64	0.27	0.29
56	neuro.ml	0.6099	0.51	37.36	614.05	0.71	0.21
57	hadi	0.8957	0.23	52.02	828.61	0.58	0.11

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