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Articles Published Processes
11/21/2025 7:06:11 AM | Browse: 3 | Download: 8
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Received |
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2025-06-09 06:03 |
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Peer-Review Started |
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2025-06-09 06:03 |
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To Make the First Decision |
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Return for Revision |
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2025-06-12 07:44 |
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Revised |
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2025-06-24 07:15 |
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Second Decision |
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2025-10-11 02:43 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2025-10-11 12:12 |
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Articles in Press |
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2025-10-11 12:12 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2025-11-17 00:15 |
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Publish the Manuscript Online |
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2025-11-21 07:06 |
| ISSN |
2218-4333 (online) |
| Open Access |
This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Radiology, Nuclear Medicine & Medical Imaging |
| Manuscript Type |
Minireviews |
| Article Title |
Lymph node disease in 2-deoxy-2-fluorodeoxyglucose positron emission tomography/computed tomography imaging: Advances in artificial intelligence-driven automatic segmentation and precise diagnosis
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Shao-Chun Li, Xin Fan and Jian He |
| ORCID |
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| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| Clinical Trials from the Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University |
2021-LCYJ-MS-11 |
| Nanjing Drum Tower Hospital National Natural Science Foundation Youth Cultivation Project |
2024-JCYJ-QP-15 |
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| Corresponding Author |
Jian He, Associate Professor, Chief Physician, MD, PhD, Department of Nuclear Medicine, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, No. 321 Zhongshan Road, Nanjing 210008, Jiangsu Province, China. hjxueren@126.com, Nanjing 210008, Jiangsu Province, China. hjxueren@163.com |
| Key Words |
Lymph node metastasis; Lymphoma; Deep learning; Convolutional neural network; Medical imaging analysis; Automatic segmentation; Radiomics |
| Core Tip |
This paper reviews the progress of 2-deoxy-2-fluorodeoxyglucose positron emission tomography/computed tomography lymph node disease diagnosis technology driven by artificial intelligence. The automatic segmentation technology based on deep learning has significantly improved the diagnostic efficiency and consistency in lymph node detection, precise segmentation and three-dimensional reconstruction, and made up for the shortcomings of poor efficiency and obvious subjectivity in traditional artificial segmentation. The deep learning model has performed well in predicting treatment responses, distinguishing benign and malignant lesions, and diagnosis of lymph node metastasis in various cancer types, providing technical support for the accurate diagnosis of lymph node diseases, individualized treatment and prognostic evaluation. |
| Publish Date |
2025-11-21 07:06 |
| Citation |
<p>Li SC, Fan X, He J. Lymph node disease in 2-deoxy-2-fluorodeoxyglucose positron emission tomography/computed tomography imaging: Advances in artificial intelligence-driven automatic segmentation and precise diagnosis. <i>World J Clin Oncol</i> 2025; 16(11): 110462</p> |
| URL |
https://www.wjgnet.com/2218-4333/full/v16/i11/110462.htm |
| DOI |
https://dx.doi.org/10.5306/wjco.v16.i11.110462 |
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