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ResearchFormerly WizWand

Binary Vessel Segmentation on CARVE 3D CT images

83.41IoUSegPL+VI
50.44259.00167.5676.119Aug 8, 2022
Updated 8mo ago

Evaluation results

MethodLinks
SegPL+VILabelled Volumes=20, Learning Paradigm=Semi-Supervised, Train(s)=1715, Flops=6.23, Para(K)=630.02022.0883.41
SegPLLabelled Volumes=20, Learning Paradigm=Semi-Supervised, Train(s)=1601, Flops=6.22, Para(K)=626.742022.0883.08
CPSLabelled Volumes=20, Learning Paradigm=Semi-Supervised, Train(s)=2730, Flops=12.44, Para(K)=1253.482022.0881.65
3D U-netLabelled Volumes=20, Learning Paradigm=Supervised, Train(s)=1014, Flops=6.22, Para(K)=626.742022.0881.4
FixMatchLabelled Volumes=20, Learning Paradigm=Semi-Supervised, Train(s)=2674, Flops=12.44, Para(K)=626.742022.0880.68
CCTLabelled Volumes=20, Learning Paradigm=Semi-Supervised, Train(s)=4129, Flops=8.3, Para(K)=646.742022.0880.58
SegPL+VILabelled Volumes=10, Learning Paradigm=Semi-Supervised, Train(s)=1715, Flops=6.23, Para(K)=630.02022.0879.73
SegPLLabelled Volumes=10, Learning Paradigm=Semi-Supervised, Train(s)=1601, Flops=6.22, Para(K)=626.742022.0879.51
SegPLLabelled Volumes=5, Learning Paradigm=Semi-Supervised, Train(s)=1601, Flops=6.22, Para(K)=626.742022.0876.52
CPSLabelled Volumes=10, Learning Paradigm=Semi-Supervised, Train(s)=2730, Flops=12.44, Para(K)=1253.482022.0875.19
SegPL+VILabelled Volumes=5, Learning Paradigm=Semi-Supervised, Train(s)=1715, Flops=6.23, Para(K)=630.02022.0873.33
FixMatchLabelled Volumes=10, Learning Paradigm=Semi-Supervised, Train(s)=2674, Flops=12.44, Para(K)=626.742022.0872.1
SegPL+VILabelled Volumes=2, Learning Paradigm=Semi-Supervised, Train(s)=1715, Flops=6.23, Para(K)=630.02022.0870.65
CPSLabelled Volumes=5, Learning Paradigm=Semi-Supervised, Train(s)=2730, Flops=12.44, Para(K)=1253.482022.0870.61
SegPLLabelled Volumes=2, Learning Paradigm=Semi-Supervised, Train(s)=1601, Flops=6.22, Para(K)=626.742022.0869.44
3D U-netLabelled Volumes=10, Learning Paradigm=Supervised, Train(s)=1014, Flops=6.22, Para(K)=626.742022.0867.93
CCTLabelled Volumes=10, Learning Paradigm=Semi-Supervised, Train(s)=4129, Flops=8.3, Para(K)=646.742022.0866.94
CPSLabelled Volumes=2, Learning Paradigm=Semi-Supervised, Train(s)=2730, Flops=12.44, Para(K)=1253.482022.0866.67
FixMatchLabelled Volumes=2, Learning Paradigm=Semi-Supervised, Train(s)=2674, Flops=12.44, Para(K)=626.742022.0862.35
FixMatchLabelled Volumes=5, Learning Paradigm=Semi-Supervised, Train(s)=2674, Flops=12.44, Para(K)=626.742022.0860.8
3D U-netLabelled Volumes=5, Learning Paradigm=Supervised, Train(s)=1014, Flops=6.22, Para(K)=626.742022.0858.28
3D U-netLabelled Volumes=2, Learning Paradigm=Supervised, Train(s)=1014, Flops=6.22, Para(K)=626.742022.0856.79
CCTLabelled Volumes=5, Learning Paradigm=Semi-Supervised, Train(s)=4129, Flops=8.3, Para(K)=646.742022.0855.32
CCTLabelled Volumes=2, Learning Paradigm=Semi-Supervised, Train(s)=4129, Flops=8.3, Para(K)=646.742022.0851.71