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CORRECTION article

Front. Oncol., 05 September 2022

Sec. Radiation Oncology

Volume 12 - 2022 | https://doi.org/10.3389/fonc.2022.1005287

Corrigendum: Investigation of a novel deep learning-based computed tomography perfusion mapping framework for functional lung avoidance radiotherapy

  • 1. Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, Hong Kong SAR, China

  • 2. Department of Nuclear Medicine, Queen Mary Hospital, Hong Kong, Hong Kong SAR, China

  • 3. School of Nursing, The Hong Kong Polytechnic University, Hong Kong, Hong Kong SAR, China

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In the published article, there was an error in the Funding statement. The funding statement for the General Research Fund was displayed as “GRF 151022/19M”. The correct Funding statement appears below.

Funding

This work is supported by the Health and Medical Research Fund (HMRF 07183266); the General Research Fund (GRF 15103520).

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.

Publisher’s note

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.

Summary

Keywords

perfusion imaging, lung function imaging, deep learning, perfusion synthesis, CT based image analysis, functional lung avoidance radiation therapy

Citation

Ren G, Lam S-k, Zhang J, Xiao H, Cheung AL-y, Ho W-y, Qin J and Cai J (2022) Corrigendum: Investigation of a novel deep learning-based computed tomography perfusion mapping framework for functional lung avoidance radiotherapy. Front. Oncol. 12:1005287. doi: 10.3389/fonc.2022.1005287

Received

28 July 2022

Accepted

12 August 2022

Published

05 September 2022

Approved by

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Volume

12 - 2022

Updates

Copyright

*Correspondence: Jing Cai,

This article was submitted to Radiation Oncology, a section of the journal Frontiers in Oncology

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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