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Related Experiment Video

Updated: May 11, 2026

Automatic Surgery in Transcatheter Aortic Valve Replacement Using Augmented Reality
07:46

Automatic Surgery in Transcatheter Aortic Valve Replacement Using Augmented Reality

Published on: August 9, 2024

Perception-first digital twin for augmented reality microsurgery.

Trishia El Chemaly1,2,3, Yunxin Fan4,5, Fanrui Fu4

  • 1Department of Bioengineering, Stanford University, Stanford, CA, USA. tchemaly@stanford.edu.

International Journal of Computer Assisted Radiology and Surgery
|May 9, 2026
PubMed
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This summary is machine-generated.

This study introduces a digital twin framework for augmented reality (AR) guidance in microsurgery. The system enhances spatial awareness by updating AR visualizations in real-time, improving surgical precision.

Area of Science:

  • Medical Engineering
  • Computer Science
  • Surgical Technology

Background:

  • Microsurgery augmented reality (AR) guidance faces challenges like depth ambiguity and limited situational awareness.
  • Digital twins offer dynamic virtual models to provide crucial contextual geometric data.
  • A perception-first digital twin framework is proposed to address these limitations in otologic surgery.

Purpose of the Study:

  • To develop and introduce a perception-first digital twin framework for AR guidance in microsurgery.
  • To leverage real-time surgical state for depth-, occlusion-, and proximity-aware AR visualization.
  • To mitigate limitations of current AR systems under the operating microscope.

Main Methods:

  • Formulated hand-eye calibration refinement using joint SE(3) optimization with robust weighting.
Keywords:
Augmented realityDigital twinOtologic surgeryStereo microscope

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Last Updated: May 11, 2026

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  • Integrated optimized calibration with high-precision optical tracking and real-time simulation for dynamic digital twin updates.
  • Utilized the updated digital twin to compute perceptual fields driving AR overlays on the microscope feed.

    • Main Results:

    • Optimized calibration achieved median translational errors of 1.06 mm and 1.19 mm, and rotational errors of 0.46° and 0.28°.
    • The digital twin successfully derived and overlaid perceptual cues onto a 3D-printed temporal bone model.
    • An AR-guided microsurgical use case demonstrated enhanced spatial understanding of critical structures and the surgical cavity.

    Conclusions:

    • A perception-first digital twin framework for AR-guided microsurgery was successfully presented.
    • The framework continuously updates the digital twin based on surgical progression to drive perception-aware AR cues.
    • The system enhances spatial understanding while maintaining operative field visibility.