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CORRECTION article

Front. Med., 06 February 2026

Sec. Ophthalmology

Volume 13 - 2026 | https://doi.org/10.3389/fmed.2026.1790647

Correction: Deep learning based optic nerve sheath diameter characterization and structure quantification on transorbital ultrasound images


Miao YangMiao Yang1Cong LiuCong Liu2Pingyang ZouPingyang Zou1Wu Wang
Wu Wang3*
  • 1Department of Anesthesiology, Guizhou Provincial People's Hospital, Guiyang, China
  • 2School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China
  • 3Electrical Engineering College, Guizhou University, Guiyang, China

The title of this article was erroneously given as: Deep Learning-based Optic Nerve Diameter Sheath Characterization and Structure Quantification on Transorbital Ultrasound Images. The correct title of the article is Deep Learning based Optic Nerve Sheath Diameter Characterization and Structure Quantification on Transorbital Ultrasound Images.

The original version of this 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.

Keywords: deep learning, optic nerve sheath diameter characterization, optic nerve segmentation, artificial intelligence, medical imaging

Citation: Yang M, Liu C, Zou P and Wang W (2026) Correction: Deep learning based optic nerve sheath diameter characterization and structure quantification on transorbital ultrasound images. Front. Med. 13:1790647. doi: 10.3389/fmed.2026.1790647

Received: 18 January 2026; Accepted: 22 January 2026;
Published: 06 February 2026.

Edited and reviewed by: Yanda Meng, University of Exeter, United Kingdom

Copyright © 2026 Yang, Liu, Zou and Wang. 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: Wu Wang, Y2hpbmEud2FuZ3d1QDE2My5jb20=

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.