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
The download links and extraction codes for our model weights are as follows: https://pan.baidu.com/s/1S_pP58kKNSz3F2B3pvLX_w 7777
The download link for the model weights on Google Drive is as follows: https://drive.google.com/drive/folders/1mIUxiqGHdDmnXm2xDH5_8feNEW9LZi6s?usp=sharing
- The SIIM-ACR dataset can be downloaded from https://www.kaggle.com/c/siim-acr-pneumothorax-segmentation/data .
- The gaze data for SIIM-ACR can be downloaded at https://github.com/HazyResearch/observational .
- The division of SIIM-ACR we based on https://github.com/MoMarky/Eye-gaze-Guided-Vision-Transformer?tab=readme-ov-file .
- The EGR-CXR dataset can be downloaded from https://physionet.org/content/egd-cxr/1.0.0/ .
The collated and processed SIIM-ACR dataset can be accessed via https://drive.google.com/file/d/1qM4LpnnBQWLr_7xlXGrUvJdaMoOjKvUS/view?usp=drive_link .
Data/<br>
├──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
@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",
}