This article is a correction to:
PI-YOLO: dynamic sparse attention and lightweight convolutional based YOLO for vessel detection in pathological images
Cong Li
Shuanlong Che2†
Youde Ding
Jianing Xi
Ling Qi- 1Affiliated Qingyuan Hospital, The Sixth Clinical Medical School, Guangzhou Medical University, Qingyuan People’s Hospital, Qingyuan, Guangdong, China
- 2Department of Pathology, Guangzhou KingMed Center for Clinical Laboratory, Guangzhou, China
- 3School of Health Management, Guangzhou Medical University, Guangzhou, China
- 4School of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China
- 5Institute of Digestive Disease, the Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People’s Hospital, Qingyuan, China
A Corrigendum on
PI-YOLO: dynamic sparse attention and lightweight convolutional based YOLO for vessel detection in pathological images
By Li C, Che S, Gong H, Ding Y, Luo Y, Xi J, Qi L and Zhang G (2024). Front. Oncol. 14:1347123. doi: 10.3389/fonc.2024.1347123
In the published article, there was an error in affiliation 1. Instead of “School of Biomedical Engineering, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People’s Hospital, Guangzhou Medical University, Guangzhou, China”, it should be “Affiliated Qingyuan Hospital, The Sixth Clinical Medical School, Guangzhou Medical University, Qingyuan People’s Hospital, Qingyuan, Guangdong, China”.
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.
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Keywords: pathological images, blood vessel, deep learning, object detection, attention mechanism
Citation: Li C, Che S, Gong H, Ding Y, Luo Y, Xi J, Qi L and Zhang G (2024) Corrigendum: PI-YOLO: dynamic sparse attention and lightweight convolutional based YOLO for vessel detection in pathological images. Front. Oncol. 14:1472621. doi: 10.3389/fonc.2024.1472621
Received: 29 July 2024; Accepted: 31 July 2024;
Published: 09 August 2024.
Approved by:
Frontiers Editorial Office, Frontiers Media SA, SwitzerlandCopyright © 2024 Li, Che, Gong, Ding, Luo, Xi, Qi and Zhang. 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: Ling Qi, qiling1718@gzhmu.edu.cn; Guiying Zhang, guiyingzhang@gzhmu.edu.cn
†These authors have contributed equally to this work