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
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 |