[MICCAI2024] Gaze-directed Vision GNN for Mitigating Shortcut Learning in Medical Image

This project contains the training and testing code for the paper, as well as the model weights trained according to our algorithm.
Paper link: https://link.springer.com/chapter/10.1007/978-3-031-72378-0_48

Model Weights

The download links and extraction codes for our model weights are as follows： https://pan.baidu.com/s/1S_pP58kKNSz3F2B3pvLX_w 7777

Dataset

1. The SIIM-ACR dataset can be downloaded from https://www.kaggle.com/c/siim-acr-pneumothorax-segmentation/data .
2. The gaze data for SIIM-ACR can be downloaded at https://github.com/HazyResearch/observational .
3. The EGR-CXR dataset can be downloaded from https://physionet.org/content/egd-cxr/1.0.0/ .

Data/
$~~$├──MIMIC_Gaze/
$~~~~~$├── test/
$~~~~~$├── gaze/
$~~~~~~~~$├── xxx.png
$~~~~~~~~$├── ...
$~~~~~$├── img/
$~~~~~~~~$├── xxx.png
$~~~~~~~~$├── ...
$~~~~~$├── train/
$~~~~~$├── gaze/
$~~~~~~~~$├── xxx.png
$~~~~~~~~$├── ...
$~~~~~$├── img/
$~~~~~~~~$├── xxx.png
$~~~~~~~~$├── ...
$~~~~~$├── mimic_part.csv

$~~$├──SIIM-ACR-Gaze/
$~~~~~$├── test/
$~~~~~$├── gaze/
$~~~~~~~~$├── xxx.png
$~~~~~~~~$├── ...
$~~~~~$├── img/
$~~~~~~~~$├── xxx.png
$~~~~~~~~$├── ...
$~~~~~$├── train/
$~~~~~$├── gaze/
$~~~~~~~~$├── xxx.png
$~~~~~~~~$├── ...
$~~~~~$├── img/
$~~~~~~~~$├── xxx.png
$~~~~~~~~$├── ...
$~~~~~$├── siim_pneumothorax.csv
$~~~~~$├── test_list.csv
$~~~~~$├── train_list.csv

Citation

@InProceedings{10.1007/978-3-031-72378-0_48,
$~~~~$ author="Wu, Shaoxuan and Zhang, Xiao and Wang, Bin and Jin, Zhuo and Li, Hansheng and Feng, Jun",
$~~~~$ title="Gaze-Directed Vision GNN for Mitigating Shortcut Learning in Medical Image",
$~~~~$ booktitle="Medical Image Computing and Computer Assisted Intervention",
$~~~~$ year="2024",
$~~~~$ publisher="Springer Nature Switzerland",
$~~~~$ pages="514--524",
}