CORRECTION article

Front. Neurosci., 15 April 2020

Sec. Brain Imaging Methods

Volume 14 - 2020 | https://doi.org/10.3389/fnins.2020.00328

Corrigendum: Improving Patch-Based Convolutional Neural Networks for MRI Brain Tumor Segmentation by Leveraging Location Information

  • 1. Vision Research Lab, Department of Electrical and Computer Engineering, University of California, Santa Barbara, Santa Barbara, CA, United States

  • 2. Department of Neurological Surgery, University of California, Irvine, Irvine, CA, United States

An author's name was incorrectly published as “Fnu Shailja.” It should be “Shailja Shailja.”

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

gliomas, brain tumor segmentation, brain parcellation atlas, convolutional neural network, DeepMedic, 3D U-Net, ensemble learning, XGBoost

Citation

Kao P-Y, Shailja S, Jiang J, Zhang A, Khan A, Chen JW and Manjunath BS (2020) Corrigendum: Improving Patch-Based Convolutional Neural Networks for MRI Brain Tumor Segmentation by Leveraging Location Information. Front. Neurosci. 14:328. doi: 10.3389/fnins.2020.00328

Received

10 March 2020

Accepted

19 March 2020

Published

15 April 2020

Approved by

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Volume

14 - 2020

Updates

Copyright

*Correspondence: Po-Yu Kao B. S. Manjunath

This article was submitted to Brain Imaging Methods, a section of the journal Frontiers in Neuroscience

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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