This repo contains the code and experiments that are implemented to contribute in MedAI Cahllenge: Transparency in Medical Image Segmentation to automate medical image segmentation while preserve transparency. In the paper below we proposed generative adversarial network-based models to segment both polyps and instruments in endoscopy images. We also provide explanations for the predictions using a layer-wise relevance propagation approach.
Explainable Medical Image Segmentation via Generative Adversarial Networks and Layer-wise Relevance Propagation, Awadelrahman Ahmed, Leen Ali, Nordic Machine Intelligence. https://journals.uio.no/NMI/article/view/9126
BibTeX:
@article{MediAI2021,
title = {{MedAI: Transparency in Medical Image Segmentation}},
author = {
Hicks, Steven and
Jha, Debesh and
Thambawita, Vajira and
Riegler, Michael and
Halvorsen, P{\aa}l and
Singstad, Bj{\o}rn-Jostein and
Gaur, Sachin and
Pettersen, Klas and
Goodwin, Morten and
Parasa, Sravanthi and
de Lange, Thomas
},
journal = {Nordic Machine Intelligence},
year = {2021},
doi = {10.5617/nmi.9140}