Binary Vessel Segmentation on CARVE 3D CT images
83.41IoUSegPL+VI
Evaluation Results
| Method | Links | |
|---|---|---|
| SegPL+VILabelled Volumes=20, Learning Paradigm=Semi-Supervised, Train(s)=1715, Flops=6.23, Para(K)=630.02022.08 | 83.41 | |
| SegPLLabelled Volumes=20, Learning Paradigm=Semi-Supervised, Train(s)=1601, Flops=6.22, Para(K)=626.742022.08 | 83.08 | |
| CPSLabelled Volumes=20, Learning Paradigm=Semi-Supervised, Train(s)=2730, Flops=12.44, Para(K)=1253.482022.08 | 81.65 | |
| 3D U-netLabelled Volumes=20, Learning Paradigm=Supervised, Train(s)=1014, Flops=6.22, Para(K)=626.742022.08 | 81.4 | |
| FixMatchLabelled Volumes=20, Learning Paradigm=Semi-Supervised, Train(s)=2674, Flops=12.44, Para(K)=626.742022.08 | 80.68 | |
| CCTLabelled Volumes=20, Learning Paradigm=Semi-Supervised, Train(s)=4129, Flops=8.3, Para(K)=646.742022.08 | 80.58 | |
| SegPL+VILabelled Volumes=10, Learning Paradigm=Semi-Supervised, Train(s)=1715, Flops=6.23, Para(K)=630.02022.08 | 79.73 | |
| SegPLLabelled Volumes=10, Learning Paradigm=Semi-Supervised, Train(s)=1601, Flops=6.22, Para(K)=626.742022.08 | 79.51 | |
| SegPLLabelled Volumes=5, Learning Paradigm=Semi-Supervised, Train(s)=1601, Flops=6.22, Para(K)=626.742022.08 | 76.52 | |
| CPSLabelled Volumes=10, Learning Paradigm=Semi-Supervised, Train(s)=2730, Flops=12.44, Para(K)=1253.482022.08 | 75.19 | |
| SegPL+VILabelled Volumes=5, Learning Paradigm=Semi-Supervised, Train(s)=1715, Flops=6.23, Para(K)=630.02022.08 | 73.33 | |
| FixMatchLabelled Volumes=10, Learning Paradigm=Semi-Supervised, Train(s)=2674, Flops=12.44, Para(K)=626.742022.08 | 72.1 | |
| SegPL+VILabelled Volumes=2, Learning Paradigm=Semi-Supervised, Train(s)=1715, Flops=6.23, Para(K)=630.02022.08 | 70.65 | |
| CPSLabelled Volumes=5, Learning Paradigm=Semi-Supervised, Train(s)=2730, Flops=12.44, Para(K)=1253.482022.08 | 70.61 | |
| SegPLLabelled Volumes=2, Learning Paradigm=Semi-Supervised, Train(s)=1601, Flops=6.22, Para(K)=626.742022.08 | 69.44 | |
| 3D U-netLabelled Volumes=10, Learning Paradigm=Supervised, Train(s)=1014, Flops=6.22, Para(K)=626.742022.08 | 67.93 | |
| CCTLabelled Volumes=10, Learning Paradigm=Semi-Supervised, Train(s)=4129, Flops=8.3, Para(K)=646.742022.08 | 66.94 | |
| CPSLabelled Volumes=2, Learning Paradigm=Semi-Supervised, Train(s)=2730, Flops=12.44, Para(K)=1253.482022.08 | 66.67 | |
| FixMatchLabelled Volumes=2, Learning Paradigm=Semi-Supervised, Train(s)=2674, Flops=12.44, Para(K)=626.742022.08 | 62.35 | |
| FixMatchLabelled Volumes=5, Learning Paradigm=Semi-Supervised, Train(s)=2674, Flops=12.44, Para(K)=626.742022.08 | 60.8 | |
| 3D U-netLabelled Volumes=5, Learning Paradigm=Supervised, Train(s)=1014, Flops=6.22, Para(K)=626.742022.08 | 58.28 | |
| 3D U-netLabelled Volumes=2, Learning Paradigm=Supervised, Train(s)=1014, Flops=6.22, Para(K)=626.742022.08 | 56.79 | |
| CCTLabelled Volumes=5, Learning Paradigm=Semi-Supervised, Train(s)=4129, Flops=8.3, Para(K)=646.742022.08 | 55.32 | |
| CCTLabelled Volumes=2, Learning Paradigm=Semi-Supervised, Train(s)=4129, Flops=8.3, Para(K)=646.742022.08 | 51.71 |