research-article

Inside-Out Instrument Tracking for Surgical Navigation in Augmented Reality

Authors:

Christina Gsaxner,

Dieter Schmalstieg,

Jan EggerAuthors Info & Claims

VRST '21: Proceedings of the 27th ACM Symposium on Virtual Reality Software and Technology

Article No.: 4, Pages 1 - 11

https://doi.org/10.1145/3489849.3489863

Published: 08 December 2021 Publication History

Abstract

Surgical navigation requires tracking of instruments with respect to the patient. Conventionally, tracking is done with stationary cameras, and the navigation information is displayed on a stationary display. In contrast, an augmented reality (AR) headset can superimpose surgical navigation information directly in the surgeon’s view. However, AR needs to track the headset, the instruments and the patient, often by relying on stationary infrastructure. We show that 6DOF tracking can be obtained without any stationary, external system by purely utilizing the on-board stereo cameras of a HoloLens 2 to track the same retro-reflective marker spheres used by current optical navigation systems. Our implementation is based on two tracking pipelines complementing each other, one using conventional stereo vision techniques, the other relying on a single-constraint-at-a-time extended Kalman filter. In a technical evaluation of our tracking approach, we show that clinically relevant accuracy of 1.70 mm/1.11° and real-time performance is achievable. We further describe an example application of our system for untethered end-to-end surgical navigation.

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cover image ACM Conferences

VRST '21: Proceedings of the 27th ACM Symposium on Virtual Reality Software and Technology

December 2021

563 pages

ISBN:9781450390927

DOI:10.1145/3489849

Editors:
Yuichi Itoh
Aoyama Gakuin University, Japan
,
Kazuki Takashima
Tohoku University, Japan
,
Parinya Punpongsanon
Osaka University, Japan
,
Misha Sra
University of California, Santa Barbara, USA
,
Kazuyuki Fujita
Tohoku University, Japan
,
Shigeo Yoshida
The University of Tokyo, Japan
,
Tham Piumsomboon
University of Canterbury, New Zealand

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December 8 - 10, 2021

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Zaccardi SArapi AFrantz TBrahimetaj RDebeuf RBeckwée DSwinnen EJansen B(2025)HoloMoCap: Real-Time Clinical Motion Capture with HoloLens 22025 IEEE International Conference on Artificial Intelligence and eXtended and Virtual Reality (AIxVR)10.1109/AIxVR63409.2025.00042(218-222)Online publication date: 27-Jan-2025
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Li JZhou ZYang JPepe AGsaxner CLuijten GQu CZhang TChen XLi WWodzinski MFriedrich PXie KJin YAmbigapathy NNasca ESolak NMelito GVu VMemon ASchlachta CDe Ribaupierre SPatel REagleson RChen XMächler HKirschke Jde la Rosa EChrist PLi HEllis DAizenberg MGatidis SKüstner TShusharina NHeller NAndrearczyk VDepeursinge AHatt MSekuboyina ALöffler MLiebl HDorent RVercauteren TShapey JKujawa ACornelissen SLangenhuizen PBen-Hamadou ARekik APujades SBoyer EBolelli FGrana CLumetti LSalehi HMa JZhang YGharleghi RBeier SSowmya AGarza-Villarreal EBalducci TAngeles-Valdez DSouza RRittner LFrayne RJi YFerrari VChatterjee SDubost FSchreiber SMattern HSpeck OHaehn DJohn CNürnberger APedrosa JFerreira CAresta GCunha ACampilho ASuter YGarcia JLalande AVandenbossche VVan Oevelen ADuquesne KMekhzoum HVandemeulebroucke JAudenaert EKrebs Cvan Leeuwen TVereecke EHeidemeyer HRöhrig RHölzle FBadeli VKrieger KGunzer MChen Jvan Meegdenburg TDada ABalzer MFragemann JJonske FRempe MMalorodov SBahnsen FSeibold CJaus AMarinov ZJaeger PStiefelhagen RSantos ALindo MFerreira AAlves VKamp MAbourayya ANensa FHörst FBrehmer AHeine LHanusrichter YWeßling MDudda MPodleska LFink MKeyl JTserpes KKim MElhabian SLamecker HZukić DPaniagua BWachinger CUrschler MDuong LWasserthal JHoyer PBasu OMaal TWitjes MSchiele GChang TAhmadi SLuo PMenze BReyes MDeserno TDavatzikos CPuladi BFua PYuille AKleesiek JEgger J(2024) MedShapeNet – a large-scale dataset of 3D medical shapes for computer vision Biomedical Engineering / Biomedizinische Technik10.1515/bmt-2024-039670:1(71-90)Online publication date: 30-Dec-2024
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