access icon openaccess Gesture-based registration correction using a mobile augmented reality image-guided neurosurgery system

In image-guided neurosurgery, a registration between the patient and their pre-operative images and the tracking of surgical tools enables GPS-like guidance to the surgeon. However, factors such as brainshift, image distortion, and registration error cause the patient-to-image alignment accuracy to degrade throughout the surgical procedure no longer providing accurate guidance. The authors present a gesture-based method for manual registration correction to extend the usage of augmented reality (AR) neuronavigation systems. The authors’ method, which makes use of the touchscreen capabilities of a tablet on which the AR navigation view is presented, enables surgeons to compensate for the effects of brainshift, misregistration, or tracking errors. They tested their system in a laboratory user study with ten subjects and found that they were able to achieve a median registration RMS error of 3.51 mm on landmarks around the craniotomy of interest. This is comparable to the level of accuracy attainable with previously proposed methods and currently available commercial systems while being simpler and quicker to use. The method could enable surgeons to quickly and easily compensate for most of the observed shift. Further advantages of their method include its ease of use, its small impact on the surgical workflow and its small-time requirement.

Inspec keywords: medical image processing; surgery; computerised tomography; brain; biomedical MRI; neurophysiology; augmented reality; image registration; mobile computing; object tracking

Other keywords: preoperative images; augmented reality neuronavigation systems; gesture-based method; surgeon; surgical tools; tablet touchscreen capability; mobile augmented reality image-guided neurosurgery system; image distortion; GPS-like guidance; manual registration correction; surgical workflow; size 3.51 mm; gesture-based registration correction; tracking errors; patient-to-image alignment accuracy; median registration RMS error; surgical procedure; brainshift

Subjects: Mobile, ubiquitous and pervasive computing; Optical, image and video signal processing; Biology and medical computing; Virtual reality; Biophysics of neurophysiological processes; X-ray techniques: radiography and computed tomography (biomedical imaging/measurement); Patient care and treatment; Patient care and treatment; Medical magnetic resonance imaging and spectroscopy; X-rays and particle beams (medical uses); Computer vision and image processing techniques; Patient diagnostic methods and instrumentation; Biomedical magnetic resonance imaging and spectroscopy

References

    1. 1)
    2. 2)
    3. 3)
    4. 4)
    5. 5)
    6. 6)
    7. 7)
      • 16. Drouin, S., Kersten-Oertel, M., Louis Collins, D.: ‘Interaction-based registration correction for improved augmented reality overlay in neurosurgery’. Workshop on Augmented Environments for Computer-Assisted Interventions, 2015, pp. 2129.
    8. 8)
    9. 9)
    10. 10)
    11. 11)
    12. 12)
    13. 13)
    14. 14)
    15. 15)
      • 22. Brooke, J.: ‘Sus-a quick and dirty usability scale’, Usability Eval. Ind., 1996, 189, (194), pp. 47.
    16. 16)
    17. 17)
      • 9. Nabavi, A., Black, P.M., Gering, D.T., et al: ‘Serial intraoperative MR imaging of brain shift’, Neurosurgery, 2001, 48, (4), pp. 787798.
    18. 18)
    19. 19)
    20. 20)
      • 18. Roethe, A. L., Rösler, J., Vajkoczy, P., et al: ‘Current experiences and future perspectives for augmented reality visualization in navigated neurosurgical interventions’, 22nd Annual Conference of the International Society for Computer Aided Surgery, Berlin, Germany, June 2018.
    21. 21)
    22. 22)
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