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@ -59,7 +59,7 @@
### Large scale Medical Image Pretrained Weights
| name | resolution | Prompt | Weights |
| Name | Resolution | Prompt | Weights |
| :---------: | :---------: | :---------: | :----------------------------------------------------------: |
| Slide-SAM-B | 1024 x 1024 | box & point | [Google Drive](https://drive.google.com/file/d/1YJ7deylSXfEwRfOAc72zBJE1xGlxSnp0/view?usp=drive_link) \| [Baidu Disk (7be9)](https://pan.baidu.com/s/1jvJ2W4MK24JdpZLwPqMIfA) |
| Slide-SAM-H | 1024 x 1024 | box & point | [Google Drive](https://drive.google.com/file/d/1KnSL5mgAdUDsktvrwcYp_9IJeqfFWhIN/view?usp=drive_link) \| [Baidu Disk (05dy)](https://pan.baidu.com/s/1jnOwyWd-M1fBIauNi3IA4w) |
@ -147,11 +147,11 @@ python -m core.volume_predictor
If the code, paper and weights help your research, please cite:
```
@inproceedings{quan2024slide,
@article{quan2023slide,
title={Slide-SAM: Medical SAM Meets Sliding Window},
author={Quan, Quan and Tang, Fenghe and Xu, Zikang and Zhu, Heqin and Zhou, S Kevin},
booktitle={Medical Imaging with Deep Learning},
year={2024}
journal={arXiv preprint arXiv:2311.10121},
year={2023}
}
```