Evidence map›Paper›PMID 40650802›Full record

ArticleInternational journal of computer assisted radiology and surgery2025

Efficient needle guidance: multi-camera augmented reality navigation without patient-specific calibration.

Yizhi Wei, Bingyu Huang, Bolin Zhao, Zhengyu Lin, Steven Zhiying Zhou

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Article in International journal of computer assisted radiology and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Yizhi Wei *School of Engineering, Huaqiao University, Quanzhou, 362021, China.ORCID http://orcid.org/0000-0003-2007-0017
Bingyu Huang *Department of Interventional Radiology, The First Affiliated Hospital of Fujian Medical university, Fuzhou, 350000, China.
Bolin ZhaoSchool of Engineering, Huaqiao University, Quanzhou, 362021, China.
Zhengyu LinDepartment of Interventional Radiology, The First Affiliated Hospital of Fujian Medical university, Fuzhou, 350000, China.
Steven Zhiying ZhouCollege of Design and Engineering, National University of Singapore, Singapore, 117575, Singapore. elezzy@nus.edu.sg.ORCID http://orcid.org/0000-0001-8455-1915

Funding

Scientific Research Funds of Huaqiao Unversity 50Y25012
6 · The paper itself

Abstract

purposeAugmented reality (AR) technology holds significant promise for enhancing surgical navigation in needle-based procedures such as biopsies and ablations. However, most existing AR systems rely on patient-specific markers, which disrupt clinical workflows and require time-consuming preoperative calibrations, thereby hindering operational efficiency and precision.

methodsWe developed a novel multi-camera AR navigation system that eliminates the need for patient-specific markers by utilizing ceiling-mounted markers mapped to fixed medical imaging devices. A hierarchical optimization framework integrates both marker mapping and multi-camera calibration. Deep learning techniques are employed to enhance marker detection and registration accuracy. Additionally, a vision-based pose compensation method is implemented to mitigate errors caused by patient movement, improving overall positional accuracy.

resultsValidation through phantom experiments and simulated clinical scenarios demonstrated an average puncture accuracy of 3.72 ± 1.21 mm. The system reduced needle placement time by 20 s compared to traditional marker-based methods. It also effectively corrected errors induced by patient movement, with a mean positional error of 0.38 pixels and an angular deviation of 0.51

conclusionThis marker-free AR guidance system significantly streamlines surgical workflows while enhancing needle navigation accuracy. Its simplicity, cost-effectiveness, and adaptability make it an ideal solution for both high- and low-resource clinical environments, offering the potential for improved precision, reduced procedural time, and better patient outcomes.

Indexed as

Augmented RealitySurgery, Computer-AssistedCalibrationEquipment DesignHumansNeedlesPhantoms, ImagingReproducibility of ResultsAugmented realityInterventional radiologyMinimally invasive surgerySurgical navigation

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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.