Multi-class Tumour Segmentation on BRATS
75.12mIoUSegPL+VI
Evaluation Results
| Method | Links | |
|---|---|---|
| SegPL+VILearning Paradigm=Semi-Supervised, Data Labelled Slices=300, Encoder Channels=162022.08 | 75.12 | |
| SegPL+VILearning Paradigm=Semi-Supervised, Data Labelled Slices=150, Encoder Channels=162022.08 | 72.93 | |
| SegPLLearning Paradigm=Semi-Supervised, Data Labelled Slices=300, Encoder Channels=162022.08 | 72.6 | |
| SegPLLearning Paradigm=Semi-Supervised, Data Labelled Slices=150, Encoder Channels=162022.08 | 71.35 | |
| CPSLearning Paradigm=Semi-Supervised, Data Labelled Slices=300, Encoder Channels=162022.08 | 71.24 | |
| SegPL+VILearning Paradigm=Semi-Supervised, Data Labelled Slices=50, Encoder Channels=162022.08 | 71.2 | |
| FixMatchLearning Paradigm=Semi-Supervised, Data Labelled Slices=300, Encoder Channels=162022.08 | 70.84 | |
| Self-LoopLearning Paradigm=Semi-Supervised, Data Labelled Slices=300, Encoder Channels=162022.08 | 70.8 | |
| SegPLLearning Paradigm=Semi-Supervised, Data Labelled Slices=50, Encoder Channels=162022.08 | 70.6 | |
| CPSLearning Paradigm=Semi-Supervised, Data Labelled Slices=150, Encoder Channels=162022.08 | 69.69 | |
| FixMatchLearning Paradigm=Semi-Supervised, Data Labelled Slices=150, Encoder Channels=162022.08 | 69.54 | |
| Self-LoopLearning Paradigm=Semi-Supervised, Data Labelled Slices=150, Encoder Channels=162022.08 | 68.45 | |
| 2D U-netLearning Paradigm=Supervised, Data Labelled Slices=300, Encoder Channels=162022.08 | 67.49 | |
| FixMatchLearning Paradigm=Semi-Supervised, Data Labelled Slices=50, Encoder Channels=162022.08 | 67.35 | |
| Self-LoopLearning Paradigm=Semi-Supervised, Data Labelled Slices=50, Encoder Channels=162022.08 | 65.91 | |
| 2D U-netLearning Paradigm=Supervised, Data Labelled Slices=150, Encoder Channels=162022.08 | 64.24 | |
| CPSLearning Paradigm=Semi-Supervised, Data Labelled Slices=50, Encoder Channels=162022.08 | 63.89 | |
| 2D U-netLearning Paradigm=Supervised, Data Labelled Slices=50, Encoder Channels=162022.08 | 54.08 |