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README.md

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+# TC-SemiSAM3-new
+
+Semi-supervised SAM3 model for coronary vessel segmentation.
+
+## Model Description
+
+This is the final checkpoint from semi-supervised training using:
+- 5 labeled videos
+- 31 unlabeled videos
+- Mean Teacher framework with temporal consistency
+
+## Usage
+
+```python
+import torch
+
+# Load checkpoint
+checkpoint = torch.load("checkpoint_final.pt", map_location="cpu")
+
+# Get student model weights
+state_dict = checkpoint["student_state_dict"]
+
+# Load into SAM3 model
+model.load_state_dict(state_dict, strict=False)
+```
+
+## Training Details
+
+- Framework: Mean Teacher + Temporal Consistency
+- Labeled data: 5 videos (140 frames)
+- Unlabeled data: 31 videos
+- Confidence-aware regularization enabled
+
+## Performance
+
+| Dataset | Dice | clDice |
+|---------|------|--------|
+| 36 Training Videos | 0.6811 | 0.7492 |
+| 36 Videos (Adaptive) | 0.7232 | 0.7775 |
+
+## Related
+
+- GitHub: https://github.com/qimingfan10/TC-SemiSAM.git