Towards markerless navigation for percutaneous needle insertions

Seitel, Alexander; Bellemann, Nadine; Hafezi, Mohammadreza; Franz, Alfred M.; Servatius, Mark; Saffari, Arash; Kilgus, Thomas; Schlemmer, Heinz Peter; Mehrabi, Arianeb; Radeleff, Boris; Maier-Hein, Lena

doi:10.1007/s11548-015-1156-7

Cited by 22 publications

(18 citation statements)

References 46 publications

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“…Previous AR instrument navigation advances examined different displaying modalities and visualisation methods. Video see-through AR experiences, created with monitors [12] and head-mounted displays [9], were developed to superimpose camera views on the injection site with needle guidance aids or radiological images. Projective AR approaches were used to project-specific navigation instructions on how to position and insert instruments [8,13].…”

Section: Related Workmentioning

confidence: 99%

HoloInjection: augmented reality support for CT‐guided spinal needle injections

Heinrich

Schwenderling

Becker

et al. 2019

Healthcare Technology Letters

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The correct placement of needles is decisive for the success of many minimally-invasive interventions and therapies. These needle insertions are usually only guided by radiological imaging and can benefit from additional navigation support. Augmented reality (AR) is a promising tool to conveniently provide needed information and may thus overcome the limitations of existing approaches. To this end, a prototypical AR application was developed to guide the insertion of needles to spinal targets using the mixed reality glasses Microsoft HoloLens. The system's registration accuracy was attempted to measure and three guidance visualisation concepts were evaluated concerning achievable in-plane and out-of-plane needle orientation errors in a comparison study. Results suggested high registration accuracy and showed that the AR prototype is suitable for reducing out-of-plane orientation errors. Limitations, like comparatively high in-plane orientation errors, effects of the viewing position and missing image slices indicate potential for improvement that needs to be addressed before transferring the application to clinical trials.

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Section: Related Workmentioning

confidence: 99%

HoloInjection: augmented reality support for CT‐guided spinal needle injections

Heinrich

Schwenderling

Becker

et al. 2019

Healthcare Technology Letters

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show abstract

“…Our results are very encouraging regarding the possibility of using Endosight as part of the clinical routine. With respect to other navigation systems [ 2 , 14 , 19 ], Endosight can potentially guide interventional procedures without the need for further real-time intraprocedure imaging (such as US or CT), thereby avoiding possible exposure to ionising radiation and the need for an additional co-registered modality. In addition, augmented reality permits to visualise on a tablet the 3D model of organs and targets superimposed upon the real patient and not on a different screen.…”

Section: Discussionmentioning

confidence: 99%

Augmented reality for interventional oncology: proof-of-concept study of a novel high-end guidance system platform

et al. 2018

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BackgroundTo assess the feasibility of a novel system that uses augmented reality to guide interventional oncology procedures.MethodsThis study was conducted in accordance to the guidelines of the local institutional review boards. Evaluation of an augmented reality system based upon a tablet, a needle handle and a set of markers was performed in three experimental models. Initially, a male anthropomorphic trunk phantom equipped with five polyvinyl chloride bars (two of 16 cm in length and 3 cm in diameter and four of 45, 30 or 20 cm in length and 2 cm in diameter) was used to study the accuracy of the system without respiratory motion or tissue compression. Next, small metallic targets were placed in a porcine model to evaluate how respiration affects the system accuracy. Finally, the performance of the system on a more complete model, a cadaver with liver metastasis, was tested.ResultsIn all experimental settings, extremely high targeting accuracy of < 5 mm in all cases was achieved: 2.0 ± 1.5 mm (mean ± standard deviation) for the anthropomorphic model, 3.9 ± 0.4 mm for the porcine model, and 2.5 mm and 2.8 mm for the two metastases in the cadaver model.ConclusionsAugmented reality can assist with needle guidance with great target accuracy for interventional procedures by simultaneously visualising three-dimensional reconstructed anatomical structures, tumour targets and interventional devices on a patient’s body, enabling performance of procedures in a simple and confident way.

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“…Markerless tracking solutions have been used experimentally on phantoms in other surgical fields. However, studies on spine surgery are lacking [11,12]. A robot system using light to track the bony anatomy and performing pedicle screw placements was recently presented.…”

Section: Introductionmentioning

confidence: 99%

Multi-view 3D skin feature recognition and localization for patient tracking in spinal surgery applications

et al. 2021

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Background Minimally invasive spine surgery is dependent on accurate navigation. Computer-assisted navigation is increasingly used in minimally invasive surgery (MIS), but current solutions require the use of reference markers in the surgical field for both patient and instruments tracking. Purpose To improve reliability and facilitate clinical workflow, this study proposes a new marker-free tracking framework based on skin feature recognition. Methods Maximally Stable Extremal Regions (MSER) and Speeded Up Robust Feature (SURF) algorithms are applied for skin feature detection. The proposed tracking framework is based on a multi-camera setup for obtaining multi-view acquisitions of the surgical area. Features can then be accurately detected using MSER and SURF and afterward localized by triangulation. The triangulation error is used for assessing the localization quality in 3D. Results The framework was tested on a cadaver dataset and in eight clinical cases. The detected features for the entire patient datasets were found to have an overall triangulation error of 0.207 mm for MSER and 0.204 mm for SURF. The localization accuracy was compared to a system with conventional markers, serving as a ground truth. An average accuracy of 0.627 and 0.622 mm was achieved for MSER and SURF, respectively. Conclusions This study demonstrates that skin feature localization for patient tracking in a surgical setting is feasible. The technology shows promising results in terms of detected features and localization accuracy. In the future, the framework may be further improved by exploiting extended feature processing using modern optical imaging techniques for clinical applications where patient tracking is crucial.

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Towards markerless navigation for percutaneous needle insertions

Abstract: Although system performance remains to be improved for clinical use, expected advances in camera technology as well as consideration of respiratory motion and automation of the individual steps will make this approach an interesting alternative for guiding percutaneous needle insertions.

Cited by 22 publications

References 46 publications

HoloInjection: augmented reality support for CT‐guided spinal needle injections

HoloInjection: augmented reality support for CT‐guided spinal needle injections

Augmented reality for interventional oncology: proof-of-concept study of a novel high-end guidance system platform

Multi-view 3D skin feature recognition and localization for patient tracking in spinal surgery applications

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