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Application of CT Multimodal Images in Rehabilitation Monitoring of Long-Distance Running

In order to monitor the rehabilitation of athletes injured in long-distance running, the author proposes a method for rehabilitation monitoring of long-distance running based on CT multimodal images. This method combines the latest multimodal image technology, integrates multimodal technology into C...

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Detalles Bibliográficos
Autores principales: Du, Xufeng, He, Yaye
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9553550/
https://www.ncbi.nlm.nih.gov/pubmed/36263095
http://dx.doi.org/10.1155/2022/6425448
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author Du, Xufeng
He, Yaye
author_facet Du, Xufeng
He, Yaye
author_sort Du, Xufeng
collection PubMed
description In order to monitor the rehabilitation of athletes injured in long-distance running, the author proposes a method for rehabilitation monitoring of long-distance running based on CT multimodal images. This method combines the latest multimodal image technology, integrates multimodal technology into CT images to improve the accuracy, performs image segmentation on CT multimodal images through medical segmentation methods, and analyzes the segmented images; finally, it can achieve the effect of rehabilitation treatment for athletes in long-distance running. Experimental results show that the total time taken by the authors' method is 10.9 hours, with an average time of 8 seconds, which is much shorter than the other two control methods. In conclusion, the authors' method allows for better rehabilitation monitoring of long-distance running sports injuries.
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spelling pubmed-95535502022-10-18 Application of CT Multimodal Images in Rehabilitation Monitoring of Long-Distance Running Du, Xufeng He, Yaye Scanning Research Article In order to monitor the rehabilitation of athletes injured in long-distance running, the author proposes a method for rehabilitation monitoring of long-distance running based on CT multimodal images. This method combines the latest multimodal image technology, integrates multimodal technology into CT images to improve the accuracy, performs image segmentation on CT multimodal images through medical segmentation methods, and analyzes the segmented images; finally, it can achieve the effect of rehabilitation treatment for athletes in long-distance running. Experimental results show that the total time taken by the authors' method is 10.9 hours, with an average time of 8 seconds, which is much shorter than the other two control methods. In conclusion, the authors' method allows for better rehabilitation monitoring of long-distance running sports injuries. Hindawi 2022-10-04 /pmc/articles/PMC9553550/ /pubmed/36263095 http://dx.doi.org/10.1155/2022/6425448 Text en Copyright © 2022 Xufeng Du and Yaye He. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Du, Xufeng
He, Yaye
Application of CT Multimodal Images in Rehabilitation Monitoring of Long-Distance Running
title Application of CT Multimodal Images in Rehabilitation Monitoring of Long-Distance Running
title_full Application of CT Multimodal Images in Rehabilitation Monitoring of Long-Distance Running
title_fullStr Application of CT Multimodal Images in Rehabilitation Monitoring of Long-Distance Running
title_full_unstemmed Application of CT Multimodal Images in Rehabilitation Monitoring of Long-Distance Running
title_short Application of CT Multimodal Images in Rehabilitation Monitoring of Long-Distance Running
title_sort application of ct multimodal images in rehabilitation monitoring of long-distance running
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9553550/
https://www.ncbi.nlm.nih.gov/pubmed/36263095
http://dx.doi.org/10.1155/2022/6425448
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