Assessing performance of augmented reality-based neurosurgical training.
Augmented reality
Neurosurgical training
Personalized virtual operative anatomy
Journal
Visual computing for industry, biomedicine, and art
ISSN: 2524-4442
Titre abrégé: Vis Comput Ind Biomed Art
Pays: Germany
ID NLM: 101759975
Informations de publication
Date de publication:
03 Jul 2019
03 Jul 2019
Historique:
received:
25
01
2019
accepted:
04
06
2019
entrez:
3
4
2020
pubmed:
3
4
2020
medline:
3
4
2020
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 32240415
doi: 10.1186/s42492-019-0015-8
pii: 10.1186/s42492-019-0015-8
pmc: PMC7099548
doi:
Types de publication
Journal Article
Langues
eng
Pagination
6Subventions
Organisme : National Natural Science Foundation of China
ID : 61802385
Organisme : Natural Science Foundation of Guangdong Province (CN)
ID : 2018A030313100
Organisme : Shenzhen Science and Technology Program
ID : JSGG20170414112714341
Organisme : Shenzhen Science and Technology Program
ID : JCYJ20170302153015013
Organisme : Research Grants Council of the Hong Kong Special Administrative Region
ID : 14225616
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