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VR/AR Technology in Human Anatomy Teaching and Operation Training
AR/VR technology can fuse the clinical imaging data and information to build an anatomical environment combining virtual and real, which is helpful to improve the interest of teaching and the learning initiative of medical students, and then improve the effect of clinical teaching. This paper studie...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8205599/ https://www.ncbi.nlm.nih.gov/pubmed/34211684 http://dx.doi.org/10.1155/2021/9998427 |
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author | Zhou, Yuan Hou, Jiejun Liu, Qi Chao, Xu Wang, Nan Chen, Yu Guan, Jianjun Zhang, Qi Diwu, Yongchang |
author_facet | Zhou, Yuan Hou, Jiejun Liu, Qi Chao, Xu Wang, Nan Chen, Yu Guan, Jianjun Zhang, Qi Diwu, Yongchang |
author_sort | Zhou, Yuan |
collection | PubMed |
description | AR/VR technology can fuse the clinical imaging data and information to build an anatomical environment combining virtual and real, which is helpful to improve the interest of teaching and the learning initiative of medical students, and then improve the effect of clinical teaching. This paper studies the application and learning effect of the VR/AR system in human anatomy surgery teaching. This paper first shows the learning environment and platform of the VR/AR system, then explains the interface and operation of the system, and evaluates the teaching situation. This paper takes the VR/AR operation simulation system of an Irish company as an example and evaluates the learning effect of 41 students in our hospital. Research shows that the introduction of the feature reweighting module in the VR/AR surgery simulation system improves the accuracy of bone structure segmentation (IOU value increases from 79.62% to 83.56%). For real human ultrasound image data, the IOU value increases from 80.21% to 82.23% after the feature reweighting module is introduced. Therefore, the dense convolution module and feature reweighting module improve the learning ability of the network for bone structure features in ultrasound images from two aspects of feature connection and importance understanding and effectively improve the performance of bone structure segmentation. |
format | Online Article Text |
id | pubmed-8205599 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-82055992021-06-30 VR/AR Technology in Human Anatomy Teaching and Operation Training Zhou, Yuan Hou, Jiejun Liu, Qi Chao, Xu Wang, Nan Chen, Yu Guan, Jianjun Zhang, Qi Diwu, Yongchang J Healthc Eng Research Article AR/VR technology can fuse the clinical imaging data and information to build an anatomical environment combining virtual and real, which is helpful to improve the interest of teaching and the learning initiative of medical students, and then improve the effect of clinical teaching. This paper studies the application and learning effect of the VR/AR system in human anatomy surgery teaching. This paper first shows the learning environment and platform of the VR/AR system, then explains the interface and operation of the system, and evaluates the teaching situation. This paper takes the VR/AR operation simulation system of an Irish company as an example and evaluates the learning effect of 41 students in our hospital. Research shows that the introduction of the feature reweighting module in the VR/AR surgery simulation system improves the accuracy of bone structure segmentation (IOU value increases from 79.62% to 83.56%). For real human ultrasound image data, the IOU value increases from 80.21% to 82.23% after the feature reweighting module is introduced. Therefore, the dense convolution module and feature reweighting module improve the learning ability of the network for bone structure features in ultrasound images from two aspects of feature connection and importance understanding and effectively improve the performance of bone structure segmentation. Hindawi 2021-06-07 /pmc/articles/PMC8205599/ /pubmed/34211684 http://dx.doi.org/10.1155/2021/9998427 Text en Copyright © 2021 Yuan Zhou et al. 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 Zhou, Yuan Hou, Jiejun Liu, Qi Chao, Xu Wang, Nan Chen, Yu Guan, Jianjun Zhang, Qi Diwu, Yongchang VR/AR Technology in Human Anatomy Teaching and Operation Training |
title | VR/AR Technology in Human Anatomy Teaching and Operation Training |
title_full | VR/AR Technology in Human Anatomy Teaching and Operation Training |
title_fullStr | VR/AR Technology in Human Anatomy Teaching and Operation Training |
title_full_unstemmed | VR/AR Technology in Human Anatomy Teaching and Operation Training |
title_short | VR/AR Technology in Human Anatomy Teaching and Operation Training |
title_sort | vr/ar technology in human anatomy teaching and operation training |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8205599/ https://www.ncbi.nlm.nih.gov/pubmed/34211684 http://dx.doi.org/10.1155/2021/9998427 |
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