From: Multi-atlas active contour segmentation method using template optimization algorithm
IBSR datasets: | Average DGM | 0.853 | Average DWM | 0.827 | |||||||
subject | DGM | DWM | subject | DGM | DWM | subject | DGM | DWM | subject | DGM | DWM |
1_24 | 0.822 | 0.803 | 2_4 | 0.829 | 0.790 | 4_8 | 0.809 | 0.803 | 5_8 | 0.806 | 0.797 |
6_10 | 0.812 | 0.793 | 7_8 | 0.832 | 0.839 | 8_4 | 0.834 | 0.817 | 11_3 | 0.889 | 0.861 |
12_3 | 0.823 | 0.855 | 13_3 | 0.877 | 0.860 | 15_3 | 0.819 | 0.773 | 16_3 | 0.869 | 0.814 |
17_3 | 0.893 | 0.822 | 100_23 | 0.897 | 0.873 | 110_3 | 0.883 | 0.810 | 111_2 | 0.875 | 0.854 |
112_2 | 0.878 | 0.865 | 191_3 | 0.866 | 0.848 | 202_3 | 0.887 | 0.833 | 205_3 | 0.855 | 0.836 |
MRBrainS13 datasets: | Average DTh | 0.927 | Average HTh | 2.923 | |||||||
subject | DTh | HTh | subject | DTh | HTh | subject | DTh | HTh | subject | DTh | HTh |
1000_3 | 0.928 | 2.828 | 1001_3 | 0.896 | 4.472 | 1002_3 | 0.914 | 3.162 | 1003_3 | 0.934 | 2.236 |
1004_3 | 0.92 | 2.828 | 1005_3 | 0.921 | 3.162 | 1006_3 | 0.92 | 3.606 | 1007_3 | 0.938 | 2.236 |
1008_3 | 0.942 | 2.828 | 1009_3 | 0.928 | 2.828 | 1010_3 | 0.916 | 3.162 | 1011_3 | 0.924 | 2.828 |
1012_3 | 0.903 | 4.123 | 1013_3 | 0.924 | 3.162 | 1014_3 | 0.941 | 2.236 | 1015_3 | 0.937 | 2.828 |
1017_3 | 0.91 | 3.606 | 1018_3 | 0.937 | 2.828 | 1019_3 | 0.957 | 1.414 | 1023_3 | 0.917 | 3.606 |
1024_3 | 0.93 | 2.828 | 1025_3 | 0.931 | 2.282 | 1036_3 | 0.94 | 2.236 | 1038_3 | 0.931 | 2.828 |
1039_3 | 0.906 | 3.606 | 1101_3 | 0.943 | 2.236 | 1104_3 | 0.936 | 2.828 | 1107_3 | 0.948 | 2.236 |
1110_3 | 0.932 | 2.828 | 1113_3 | 0.937 | 2.828 | 1116_3 | 0.918 | 3.606 | 1119_3 | 0.915 | 3.162 |
1122_3 | 0.921 | 3.162 | 1125_3 | 0.907 | 2.828 | 1128_3 | 0.938 | 2.828 |