Student Become Decathlon Master in Retinal Vessel Segmentation via Dual-teacher Multi-target Domain Adaptation
Pytorch implementation for our multi-target domain adaptation method with application to retinal vessel segmentation. We use style transfer, style augmentation and dual-teacher knowledge distillation to train a domain-generic student on multiple domains.
Please cite our paper if you find the code or dataset useful for your research.
You can download our dataset mmRV via this link.
The detailed information is listed in the following table.
| Modality | Original Dataset | Train:Test | Size |
|---|---|---|---|
| OCTA | OCTA-500 | 395:50 | 384×384 |
| OCTA | ROSE | 30:9 | 304×304 |
| OCT | OCTA-500 | 395:50 | 384×384 |
| Fundus Image | DRIVE | 34:36 | 512×512 |
| Fundus Image | HRF | 30:15 | 512×512 |
| UWF Fundus | PRIME-FP20 | 40:20 | 512×512 |
- Python 3.8+
- Pytorch 1.8+
- tensorboardX