Cargando…
Assessing performance of augmented reality-based neurosurgical training
This paper presents a novel augmented reality (AR)-based neurosurgical training simulator which provides a very natural way for surgeons to learn neurosurgical skills. Surgical simulation with bimanual haptic interaction is integrated in this work to provide a simulated environment for users to achi...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Singapore
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7099548/ https://www.ncbi.nlm.nih.gov/pubmed/32240415 http://dx.doi.org/10.1186/s42492-019-0015-8 |
_version_ | 1783511327031951360 |
---|---|
author | Si, Wei-Xin Liao, Xiang-Yun Qian, Yin-Ling Sun, Hai-Tao Chen, Xiang-Dong Wang, Qiong Heng, Pheng Ann |
author_facet | Si, Wei-Xin Liao, Xiang-Yun Qian, Yin-Ling Sun, Hai-Tao Chen, Xiang-Dong Wang, Qiong Heng, Pheng Ann |
author_sort | Si, Wei-Xin |
collection | PubMed |
description | This paper presents a novel augmented reality (AR)-based neurosurgical training simulator which provides a very natural way for surgeons to learn neurosurgical skills. Surgical simulation with bimanual haptic interaction is integrated in this work to provide a simulated environment for users to achieve holographic guidance for pre-operative training. To achieve the AR guidance, the simulator should precisely overlay the 3D anatomical information of the hidden target organs in the patients in real surgery. In this regard, the patient-specific anatomy structures are reconstructed from segmented brain magnetic resonance imaging. We propose a registration method for precise mapping of the virtual and real information. In addition, the simulator provides bimanual haptic interaction in a holographic environment to mimic real brain tumor resection. In this study, we conduct AR-based guidance validation and a user study on the developed simulator, which demonstrate the high accuracy of our AR-based neurosurgery simulator, as well as the AR guidance mode’s potential to improve neurosurgery by simplifying the operation, reducing the difficulty of the operation, shortening the operation time, and increasing the precision of the operation. |
format | Online Article Text |
id | pubmed-7099548 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer Singapore |
record_format | MEDLINE/PubMed |
spelling | pubmed-70995482020-03-31 Assessing performance of augmented reality-based neurosurgical training Si, Wei-Xin Liao, Xiang-Yun Qian, Yin-Ling Sun, Hai-Tao Chen, Xiang-Dong Wang, Qiong Heng, Pheng Ann Vis Comput Ind Biomed Art Original Article This paper presents a novel augmented reality (AR)-based neurosurgical training simulator which provides a very natural way for surgeons to learn neurosurgical skills. Surgical simulation with bimanual haptic interaction is integrated in this work to provide a simulated environment for users to achieve holographic guidance for pre-operative training. To achieve the AR guidance, the simulator should precisely overlay the 3D anatomical information of the hidden target organs in the patients in real surgery. In this regard, the patient-specific anatomy structures are reconstructed from segmented brain magnetic resonance imaging. We propose a registration method for precise mapping of the virtual and real information. In addition, the simulator provides bimanual haptic interaction in a holographic environment to mimic real brain tumor resection. In this study, we conduct AR-based guidance validation and a user study on the developed simulator, which demonstrate the high accuracy of our AR-based neurosurgery simulator, as well as the AR guidance mode’s potential to improve neurosurgery by simplifying the operation, reducing the difficulty of the operation, shortening the operation time, and increasing the precision of the operation. Springer Singapore 2019-07-03 /pmc/articles/PMC7099548/ /pubmed/32240415 http://dx.doi.org/10.1186/s42492-019-0015-8 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Article Si, Wei-Xin Liao, Xiang-Yun Qian, Yin-Ling Sun, Hai-Tao Chen, Xiang-Dong Wang, Qiong Heng, Pheng Ann Assessing performance of augmented reality-based neurosurgical training |
title | Assessing performance of augmented reality-based neurosurgical training |
title_full | Assessing performance of augmented reality-based neurosurgical training |
title_fullStr | Assessing performance of augmented reality-based neurosurgical training |
title_full_unstemmed | Assessing performance of augmented reality-based neurosurgical training |
title_short | Assessing performance of augmented reality-based neurosurgical training |
title_sort | assessing performance of augmented reality-based neurosurgical training |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7099548/ https://www.ncbi.nlm.nih.gov/pubmed/32240415 http://dx.doi.org/10.1186/s42492-019-0015-8 |
work_keys_str_mv | AT siweixin assessingperformanceofaugmentedrealitybasedneurosurgicaltraining AT liaoxiangyun assessingperformanceofaugmentedrealitybasedneurosurgicaltraining AT qianyinling assessingperformanceofaugmentedrealitybasedneurosurgicaltraining AT sunhaitao assessingperformanceofaugmentedrealitybasedneurosurgicaltraining AT chenxiangdong assessingperformanceofaugmentedrealitybasedneurosurgicaltraining AT wangqiong assessingperformanceofaugmentedrealitybasedneurosurgicaltraining AT hengphengann assessingperformanceofaugmentedrealitybasedneurosurgicaltraining |