Evidence map›Paper›PMID 31915014›Full record

ArticleBiomedical engineering online2020

Optimization of virtual and real registration technology based on augmented reality in a surgical navigation system.

Long Chen, Fengfeng Zhang, Wei Zhan, Minfeng Gan, Lining Sun

Abstract read
In one paragraph

Article in Biomedical engineering online, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Long ChenSchool of Mechanical and Electrical Engineering, Soochow University, Suzhou, 215006, China.
Fengfeng ZhangSchool of Mechanical and Electrical Engineering, Soochow University, Suzhou, 215006, China. zhangfengfeng@suda.edu.cn.
Wei ZhanDepartment of Radiation Oncology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Minfeng GanDepartment of Radiation Oncology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Lining SunSchool of Mechanical and Electrical Engineering, Soochow University, Suzhou, 215006, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe traditional navigation interface was intended only for two-dimensional observation by doctors; thus, this interface does not display the total spatial information for the lesion area. Surgical navigation systems have become essential tools that enable for doctors to accurately and safely perform complex operations. The image navigation interface is separated from the operating area, and the doctor needs to switch the field of vision between the screen and the patient's lesion area. In this paper, augmented reality (AR) technology was applied to spinal surgery to provide more intuitive information to surgeons. The accuracy of virtual and real registration was improved via research on AR technology. During the operation, the doctor could observe the AR image and the true shape of the internal spine through the skin.

methodsTo improve the accuracy of virtual and real registration, a virtual and real registration technique based on an improved identification method and robot-assisted method was proposed. The experimental method was optimized by using the improved identification method. X-ray images were used to verify the effectiveness of the puncture performed by the robot.

resultsThe final experimental results show that the average accuracy of the virtual and real registration based on the general identification method was 9.73 ± 0.46 mm (range 8.90-10.23 mm). The average accuracy of the virtual and real registration based on the improved identification method was 3.54 ± 0.13 mm (range 3.36-3.73 mm). Compared with the virtual and real registration based on the general identification method, the accuracy was improved by approximately 65%. The highest accuracy of the virtual and real registration based on the robot-assisted method was 2.39 mm. The accuracy was improved by approximately 28.5% based on the improved identification method.

conclusionThe experimental results show that the two optimized methods are highly very effective. The proposed AR navigation system has high accuracy and stability. This system may have value in future spinal surgeries.

Indexed as

Augmented RealityVirtual RealityHumansRoboticsSoftwareSpineSurgery, Computer-AssistedAugmented realityImproved identification methodRobotSurgical navigationVirtual and real registration

Identifiers

PMID31915014
PMCPMC6950982

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.