| --- |
| tags: |
| - model_hub_mixin |
| - pytorch_model_hub_mixin |
| license: mit |
| --- |
| |
| ## A Reality Check of Vision-Language Pre-training in Radiology: Have We Progressed Using Text? |
|
|
| - Code: [DLILP](https://github.com/jusiro/DLILP) |
| - Paper: [IPMI 2025](https://link.springer.com/chapter/10.1007/978-3-031-96625-5_20) - [ArXiv](https://arxiv.org/abs/2504.05227) |
| - Docs: [Documentation](https://github.com/jusiro/DLILP) |
| - Tutorial: [Notebook](https://colab.research.google.com/drive/1_8Ysd8mCKuLX_Q86e-7pOAHFbSR9F4aZ?usp=sharing) |
|
|
| ### About "CXR_Unimodal_CMP" weights: |
|
|
| - A vision encoder for CXR pre-trained using only a vision encoder, via labels extracted trough NER extraction methods. |
| - Pre-trained on CheXpert, MIMIC, and PadChest data. |
|
|
| If you find this repository useful, please consider citing this paper: |
| ``` |
| @inproceedings{dlilp, |
| title={A Reality Check of Vision-Language Pre-training in Radiology: Have We Progressed Using Text?}, |
| author={Julio Silva-Rodríguez and Jose Dolz and Ismail {Ben Ayed}}, |
| booktitle={Information Processing in Medical Imaging (IPMI)}, |
| year={2025} |
| } |
| ``` |
