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Articles Published Processes
6/19/2023 6:39:30 AM | Browse: 83 | Download: 121
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Received |
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2023-02-15 15:40 |
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Peer-Review Started |
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2023-02-15 15:42 |
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To Make the First Decision |
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Return for Revision |
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2023-03-24 02:44 |
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Revised |
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2023-04-06 10:29 |
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Second Decision |
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2023-05-05 03:09 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Company Editor-in-Chief |
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2023-05-06 02:35 |
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Articles in Press |
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2023-05-06 02:35 |
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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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2023-05-31 00:17 |
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Publish the Manuscript Online |
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2023-06-19 06:39 |
| ISSN |
2218-5836 (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: http://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
©The Author(s) 2023. 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 |
Orthopedics |
| Manuscript Type |
Basic Study |
| Article Title |
Automated patellar height assessment on high-resolution radiographs with a novel deep learning-based approach
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Kamil Kwolek, Dariusz Grzelecki, Konrad Kwolek, Dariusz Marczak, Jacek Kowalczewski and Marcin Tyrakowski |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Kamil Kwolek, MD, Academic Research, Doctor, Surgeon, Department of Spine Disorders and Orthopaedics, Centre of Postgraduate Medical Education, Gruca Orthopaedic and Trauma Teaching Hospital, Konarskiego 13, Otwock 05-400, Poland. kwolekamil@gmail.com |
| Key Words |
Medical imaging; Artificial intelligence in orthopedics; Patellar index; Deep learning; Bone segmentation; Region of interest detection |
| Core Tip |
This study presents an accurate method for automatic assessment of patellar height on high-resolution lateral knee radiographs. First, You Only Look Once neural network is used to detect patellar and proximal tibial region. Next, U-Net neural network is utilized to segment bones of the detected region. Then, the Caton-Deschamps and Blackburne-Peel indexes are calculated upon patellar end-points and joint line fitted to proximal tibia joint surface. Experimental results show that our approach has the potential to be used as a pre- and postoperative assessment tool. |
| Publish Date |
2023-06-19 06:39 |
| Citation |
Kwolek K, Grzelecki D, Kwolek K, Marczak D, Kowalczewski J, Tyrakowski M. Automated patellar height assessment on high-resolution radiographs with a novel deep learning-based approach. World J Orthop 2023; 14(6): 387-398 |
| URL |
https://www.wjgnet.com/2218-5836/full/v14/i6/387.htm |
| DOI |
https://dx.doi.org/10.5312/wjo.v14.i6.387 |
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