Skip to main content

MARIN: an open-source mobile augmented reality interactive neuronavigation system



Neuronavigation systems making use of augmented reality (AR) have been the focus of much research in the last couple of decades. In recent years, there has been considerable interest in using mobile devices for AR in the operating room (OR). We propose a complete system that performs real-time AR video augmentation on a mobile device in the context of image-guided neurosurgery.


MARIN (mobile augmented reality interactive neuronavigation system) improves upon the state of the art in terms of performance, allowing real-time augmentation, and interactivity by allowing users to interact with the displayed data. The system was tested in a user study with 17 subjects for qualitative and quantitative evaluation in the context of target localization and brought into the OR for preliminary feasibility tests, where qualitative feedback from surgeons was obtained.


The results of the user study showed that MARIN performs significantly better in terms of both time (\(p <0.0004\)) and accuracy (\(p <0.04\)) for the task of target localization in comparison with a traditional image-guided neurosurgery (IGNS) navigation system. Further, MARIN AR visualization was found to be more intuitive and allowed users to estimate target depth more easily.


MARIN improves upon previously proposed mobile AR neuronavigation systems with its real-time performance, higher accuracy, full integration in the normal workflow and greater interactivity and customizability of the displayed information. The improvement in efficiency and usability over previous systems will facilitate bringing AR into the OR.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7


  1. Carbone M, Piazza R, Condino S (2020) Commercially available head- mounted displays are unsuitable for augmented reality surgical guidance: a call for focused research for surgical applications. Surg Innov.

    Article  PubMed  Google Scholar 

  2. Deng W, Li F, Wang M, Song Z (2014) Easy-to-use augmented reality neuronavigation using a wireless tablet PC. Stereotact Funct Neurosurg 92(1):17–24

    Article  Google Scholar 

  3. Drouin S, Kersten-Oertel M, Chen SJS, Collins DL (2012) A realistic test and development environment for mixed reality in neurosurgery. In: Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics), vol 7264 LNCS, pp 13–23.

  4. Drouin S, Kochanowska A, Kersten-Oertel M, Gerard IJ, Zelmann R, De Nigris D, Bériault S, Arbel T, Sirhan D, Sadikot AF, Hall JA, Sinclair DS, Petrecca K, DelMaestro RF, Collins DL (2016) IBIS: an OR ready open-source platform for image-guided neurosurgery. Int J Comput Assist Radiol Surg 12(3):363–378.

    Article  PubMed  Google Scholar 

  5. Eftekhar B (2016) A smartphone app to assist scalp localization of superficial supratentorial lesions—technical note. World Neurosurg 85:359–363.

    Article  PubMed  Google Scholar 

  6. Faul F, Erdfelder E, Buchner A, Lang AG (2009) Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behav Res Methods 41(4):1149–1160.

    Article  PubMed  Google Scholar 

  7. Galloway RL Jr (2001) The process and development of image-guided procedures. Ann Rev Biomed Eng 3(1):83–108

    CAS  Article  Google Scholar 

  8. Galloway RL Jr, Peters T (2008) Overview and history of image-guided interventions. In: Peters T, Cleary K (eds) Image-guided interventions: technology and applications (chap. 1). Springer, Berlin, pp 1–16

    Google Scholar 

  9. Hart SG, Staveland LE (1988) Development of NASA-TLX (Task Load Index): results of empirical and theoretical research. Adv Psychol 52:139–183

    Article  Google Scholar 

  10. Hou Y, Ma L, Zhu R, Chen X, Zhang J (2016) A low-cost iphone-assisted augmented reality solution for the localization of intracranial lesions. PLoS ONE 11(7):1–18.

    CAS  Article  Google Scholar 

  11. Kersten-Oertel M, Gerard IJ, Drouin S, Mok K, Sirhan D, Sinclair DS, Collins DL (2015) Augmented reality for specific neurovascular surgical tasks. In: Workshop on augmented environments for computer-assisted interventions, Springer, pp 92–103

  12. Lasso A, Heffter T, Rankin A, Pinter C, Ungi T, Fichtinger G (2014) PLUS: Open-source toolkit for ultrasound-guided intervention systems. IEEE Trans Biomed Eng.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Léger É, Drouin S, Collins DL, Popa T, Kersten-Oertel M (2017) Quantifying attention shifts in augmented reality image-guided neurosurgery. Healthc Technol Lett 4(5):188–192.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Léger É, Reyes J, Drouin S, Collins DL, Popa T, Kersten-Oertel M (2018) Gesture-based registration correction using a mobile augmented reality image-guided neurosurgery system. Healthc Technol Lett 5(5):137–142.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Leibinger A, Forte AE, Tan Z, Oldfield MJ, Beyrau F, Dini D, Rodriguez y Baena F (2016) Soft tissue phantoms for realistic needle insertion: a comparative study. Ann Biomed Eng 44(8):2442–2452.

    Article  PubMed  Google Scholar 

  16. Roberts DW, Strohbehn JW, Hatch JF, Murray W, Kettenberger H (1986) A frameless stereotaxic integration of computerized tomographic imaging and the operating microscope. J Neurosurg 65(4):545–549.

    CAS  Article  PubMed  Google Scholar 

  17. Sielhorst T, Feuerstein M, Navab N (2008) Advanced medical displays: a literature review of augmented reality. J Disp Technol 4(4):451–467

    Article  Google Scholar 

  18. Tokuda J, Fischer GS, Papademetris X, Yaniv Z, Ibanez L, Cheng P, Liu H, Blevins J, Arata J, Golby AJ, Kapur T, Pieper S, Burdette EC, Fichtinger G, Tempany CM, Hata N (2009) OpenIGTLink: an open network protocol for image-guided therapy environment. Int J Med Robot Comput Assis Surg 5(4):423–434.

    Article  Google Scholar 

  19. Ungi T, Lasso A, Fichtinger G (2016) Open-source platforms for navigated image-guided interventions. Med Image Anal 33:181–186.

    Article  PubMed  Google Scholar 

  20. Watanabe E, Satoh M, Konno T, Hirai M, Yamaguchi T (2016) The trans-visible navigator: a see-through neuronavigation system using augmented reality. World Neurosurg 87:399–405.

    Article  PubMed  Google Scholar 

  21. Zhang Z (2000) A flexible new technique for camera calibration. IEEE Trans Pattern Anal Mach Intell 22(11):1330–1334.

    Article  Google Scholar 

Download references


This work was supported by the Fond de recherche du Québec - Nature et technologie and the Natural Sciences and Engineering Research Council of Canada.


Funding was provided by the Natural Sciences and Engineering Research Council of Canada (Grant Number n01573) and Fonds de Recherche du Québec - Nature et Technologies (Grant Number FE0223).

Author information

Authors and Affiliations


Corresponding author

Correspondence to Étienne Léger.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the University Human Research Ethics Committee (Certification Number: 30007443).

Informed consent

Informed consent was obtained from all participants included in the study.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Léger, É., Reyes, J., Drouin, S. et al. MARIN: an open-source mobile augmented reality interactive neuronavigation system. Int J CARS 15, 1013–1021 (2020).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:


  • Image-guided intervention
  • Mobile
  • Augmented reality
  • Neuronavigation
  • Interactive