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Audiovisual AR concepts for laparoscopic subsurface structure navigation

Fabian Joeres (Otto-von-Guericke University, Germany), David Black (Otto-von-Guericke University, Germany), Seyedsina Razavizadeh (Otto-von-Guericke University, Germany), Christian Hansen (Otto-von-Guericke University, Germany)


Proceedings of Graphics Interface 2021:
Virtual Event,
28 – 29 May 2021, pp. 224 – 230

Abstract

The identification of subsurface structures during resection wound repair is a challenge during minimally invasive partial nephrectomy. Specifically, major blood vessels and branches of the urinary collecting system need to be localized under time pressure as target or risk structures during suture placement. This work presents concepts for AR visualization and auditory guidance based on tool position that support this task. We evaluated the concepts in a laboratory user study with a simplified, simulated task: The localization of subsurface target points in a healthy kidney phantom. We evaluated the task time, localization accuracy, and perceived workload for our concepts and a control condition without navigation support. The AR visualization improved the accuracy and perceived workload over the control condition. We observed similar, non-significant trends for the auditory display. Further, clinically realistic evaluation is pending. Our initial results indicate the potential benefits of our concepts in supporting laparoscopic resection wound repair.

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