@inproceedings{891fb6046c514e08a295921acfcbad0d,
title = "Extending Probabilistic U-Net Using MC-Dropout to Quantify Data and Model Uncertainty",
abstract = "We extend the Probabilistic U-Net using MC-Dropout to estimate model uncertainty in addition to the data uncertainty in order to improve the overall predictive uncertainty estimate. We use this model on the datasets present in the QUBIQ21 challenge and achieve a mean score of 0.719.",
author = "Ishaan Bhat and Kuijf, {Hugo J.}",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 7th International Brain Lesion Workshop, BrainLes 2021, held in conjunction with the Medical Image Computing and Computer Assisted Intervention, MICCAI 2021 ; Conference date: 27-09-2021 Through 27-09-2021",
year = "2022",
doi = "10.1007/978-3-031-09002-8_48",
language = "English",
isbn = "9783031090011",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "555--559",
editor = "Alessandro Crimi and Spyridon Bakas",
booktitle = "Brainlesion",
address = "Germany",
}