/CLIP-Lung

CLIP-Lung (MICCAI 2023)

Primary LanguagePython

CLIP-Lung

This repository is about the paper ``CLIP-Lung: Textual Knowledge-Guided Lung Nodule Malignancy Prediction'' published at MICCAI 2023.

Dataset

Please customize your own Class of Dataset. In our implementation, the __getitem__ function returns a triplet of image tensor, class label, and attribute weights.

Training

bash run.sh

Citation

If you find the code useful for your research, please consider citing

@inproceedings{
  lei2023cliplung,
  title={CLIP-Lung: Textual Knowledge-Guided Lung Nodule Malignancy Prediction},
  author={Lei Yiming and Li Zilong and Shen Yan and Zhang Junping and Shan Hongming},
  booktitle={Medical Image Computing and Computer Assisted Intervention -- MICCAI 2023},
  year={2023},
  pages={403--412}
}