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CORRECTION article

Front. Neurosci., 15 April 2020
Sec. Brain Imaging Methods
Volume 14 - 2020 | https://doi.org/10.3389/fnins.2020.00328
This article is part of the Research Topic Multimodal Brain Tumor Segmentation and Beyond View all 28 articles

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

This article is a correction to:

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

    1. Read original article
\nPo-Yu Kao Po-Yu Kao1*Shailja ShailjaShailja Shailja1Jiaxiang JiangJiaxiang Jiang1Angela ZhangAngela Zhang1Amil KhanAmil Khan1Jefferson W. ChenJefferson W. Chen2B. S. Manjunath B. S. Manjunath1*
  • 1Vision Research Lab, Department of Electrical and Computer Engineering, University of California, Santa Barbara, Santa Barbara, CA, United States
  • 2Department of Neurological Surgery, University of California, Irvine, Irvine, CA, United States

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

by Kao, P.-Y., Shailja, S., Jiang, J., Zhang, A., Khan, A., Chen, J. W., et al. (2020). Front. Neurosci. 13:1449. doi: 10.3389/fnins.2019.01449

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.

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

Copyright © 2020 Kao, Shailja, Jiang, Zhang, Khan, Chen and Manjunath. 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: Po-Yu Kao, poyu_kao@ucsb.edu; B. S. Manjunath, manj@ucsb.edu

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.