In the original article, we neglected to include the funder Robert Bosch Center for Data Science and Artificial Intelligence (RBCDSAI), CR1920ED617RBCX008562.
We would like to add the above grant information to the Acknowledgment section as follows:
“This work was funded by the Robert Bosch Center for Data Science and Artificial Intelligence (RBCDSAI), under project number CR1920ED617RBCX008562 (Interpretability for Deep Learning Models in Healthcare).”
The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.
Summary
Keywords
interpretability, CNN, brain tumor, segmentation, uncertainty, activation maps, features, explainability
Citation
Natekar P, Kori A and Krishnamurthi G (2021) Corrigendum: Demystifying Brain Tumor Segmentation Networks: Interpretability and Uncertainty Analysis. Front. Comput. Neurosci. 15:651959. doi: 10.3389/fncom.2021.651959
Received
11 January 2021
Accepted
12 January 2021
Published
29 January 2021
Approved by
Frontiers Editorial Office, Frontiers Media SA, Switzerland
Volume
15 - 2021
Updates
Copyright
© 2021 Natekar, Kori and Krishnamurthi.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Ganapathy Krishnamurthi gankrish@iitm.ac.in
Disclaimer
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