Domain Transfer Through Image-to-Image Translation in Prostate Cancer Detection

We further extend our method by incoperating the uncertainty estimation to the model to improve the classification performance. To this end, we further propose the Evidential Focal Loss as a loss function for binary prostate cancer classification. The extended journal version is available at here

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@conference{Zhou2022,
title = {Domain Transfer through Image-to-Image Translation in Prostate Cancer Detection},
author = {Meng Zhou and Amoon Jamzad and Jason Izard and Alexandre Menard and Robert Siemens and Parvin Mousavi},
year = {2022},
date = {2022-03-22},
booktitle = {20th Annual Symposium of the Imaging Network of Ontario (ImNO) 2022},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}

@article{zhou2023domain,
  title={Domain Transfer Through Image-to-Image Translation for Uncertainty-Aware Prostate Cancer Classification},
  author={Zhou, Meng and Jamzad, Amoon and Izard, Jason and Menard, Alexandre and Siemens, Robert and Mousavi, Parvin},
  journal={arXiv preprint arXiv:2307.00479},
  year={2023}
}