This is the Pytorch implementation of LUCAS: LUng CAncer Screening with Multimodal Biomarkers presented at the Multimodal Learning for Clinical Decision Support workshop ML-CDS in MICCAI, 2020.
You can access the LUCAS dataset, corresponding annotations, and pretrained models following this link
Requirements:
- Python >= 3.6
- Pytorch == 1.4
- Numpy
- NiBabel
- Apex (optional, for Automatic Mixed Precision training)
@inproceedings{daza2020lucas,
title={LUCAS: LUng CAncer Screening with Multimodal Biomarkers},
author={Daza, Laura and Castillo, Angela and Escobar, Maria and Valencia, Sergio and Pinz{\'o}n, Bibiana and Arbel{\'a}ez, Pablo},
booktitle={Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures},
pages={115--124},
year={2020},
organization={Springer}
}
This project was partially supported by the Google Latin America Research Awards (LARA) 2019.