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Correction to: Automatic differentiation of Glaucoma visual field from non-glaucoma visual field using deep convolutional neural network

BMC Medical Imaging volume 19, Article number: 40 (2019) Cite this article

The Original Article was published on 04 October 2018

Correction to: BMC Med Imaging (2018) 18: 35

https://doi.org/10.1186/s12880-018-0273-5

In the original version of this article [1], published on 4 October 2018, there was an error in the article title. The title of the original publication is: “Automatic differentiation of Glaucoma visual field from non-glaucoma visual filed using deep convolutional neural network”, however, the correct title should be: “Automatic differentiation of Glaucoma visual field from non-glaucoma visual field using deep convolutional neural network”, as presented in the title of this Correction article.

The same error appears in the Background section of the Abstract. "To develop a deep neural network able to differentiate glaucoma from non-glaucoma visual fields based on visual filed (VF) test results, we collected VF tests from 3 different ophthalmic centers in mainland China" should instead read: "To develop a deep neural network able to differentiate glaucoma from non-glaucoma visual fields based on visual field (VF) test results, we collected VF tests from 3 different ophthalmic centers in mainland China".

Reference

  1. Li F, Wang Z, Qu G, et al. Automatic differentiation of Glaucoma visual field from non-glaucoma visual filed using deep convolutional neural network. BMC Med Imaging. 2018;18(35) https://doi.org/10.1186/s12880-018-0273-5.

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Author notes

  1. Fei Li, Zhe Wang and Guoxiang Qu contributed equally to this work.

Authors and Affiliations

  1. Zhongshan Ophthalmic Center, State Key Laboratory of Ophthalmology, Sun Yat-sen University, Guangzhou, China

    Fei Li, Ye Yuan, Kai Gao, Guangwei Luo & Xiulan Zhang

  2. Guangdong key lab of Computer Vision & Virtual Reality, Multimedia Research Center, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Guoxiang Qu, Diping Song, Zegu Xiao & Yu Qiao

  3. Department of Ophthalmology, The First Affiliated Hospital of Kunming Medical University, Kunming, China

    Yang Xu & Hua Zhong

  4. SenseTime Group Limited, Hong Kong, China

    Zhe Wang

  5. C-MER Dennis Lam Eye Hospital, Shenzhen, China

    Ye Yuan & Dennis S. C. Lam

Authors
  1. Fei Li
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  2. Zhe Wang
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  3. Guoxiang Qu
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  4. Diping Song
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  5. Ye Yuan
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  6. Yang Xu
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  7. Kai Gao
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  8. Guangwei Luo
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  9. Zegu Xiao
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  10. Dennis S. C. Lam
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  11. Hua Zhong
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  12. Yu Qiao
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  13. Xiulan Zhang
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Corresponding authors

Correspondence to Hua Zhong, Yu Qiao or Xiulan Zhang.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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Li, F., Wang, Z., Qu, G. et al. Correction to: Automatic differentiation of Glaucoma visual field from non-glaucoma visual field using deep convolutional neural network. BMC Med Imaging 19, 40 (2019). https://doi.org/10.1186/s12880-019-0339-z

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  • DOI: https://doi.org/10.1186/s12880-019-0339-z

BMC Medical Imaging

ISSN: 1471-2342

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