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## Dataset: **OAIZIB-CM**
| Source | link |
| ------------ | ------------------------------------------------------------ |
| Google Drive | [here](https://drive.google.com/drive/folders/13_afAKSH7ZMOI_Nk2gfoihbJKwafw1l9?usp=share_link) |
| Huggingface | [here](https://huggingface.co/datasets/YongchengYAO/OAIZIB-CM/tree/main) |
If you use our preprocessed data, please note that the manual segmentation annotations come from this work:
- Automated Segmentation of Knee Bone and Cartilage combining Statistical Shape Knowledge and Convolutional Neural Networks: Data from the Osteoarthritis Initiative (https://doi.org/10.1016/j.media.2018.11.009)
<br/><br/>
## Download from Huggingface
```bash
#!/bin/bash
pip install huggingface-hub[cli]
huggingface-cli login --token $HF_TOKEN
```
```python
# python
from huggingface_hub import snapshot_download
snapshot_download(repo_id="YongchengYAO/OAIZIB-CM", repo_type='dataset', local_dir="/your/local/folder")
```
<br/><br/>
## Files
### Images & Labels
- imagesTr: training images (#404)
- labelsTr: training segmentation masks (#404)
- imagesTs: testing images (#103)
- labelsTs: testing segmentation masks (#103)
### Data Split & Info
- `subInfo_train.xlsx`: list of training data
- `subInfo_test.xlsx`: list of testing data
- `kneeSideInfo.csv`: a file containing knee side information, used in CartiMorph Toolbox
<br/><br/>
## Paper
```
@article{YAO2024103035,
title = {CartiMorph: A framework for automated knee articular cartilage morphometrics},
journal = {Medical Image Analysis},
author = {Yongcheng Yao and Junru Zhong and Liping Zhang and Sheheryar Khan and Weitian Chen},
volume = {91},
pages = {103035},
year = {2024},
issn = {1361-8415},
doi = {https://doi.org/10.1016/j.media.2023.103035}
}
```
```
@misc{yao2024quantifyingkneecartilageshape,
title={Quantifying Knee Cartilage Shape and Lesion: From Image to Metrics},
author={Yongcheng Yao and Weitian Chen},
year={2024},
eprint={2409.07361},
archivePrefix={arXiv},
primaryClass={eess.IV},
url={https://arxiv.org/abs/2409.07361},
}
```
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