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Related Experiment Video

Updated: Jun 7, 2026

Technical Approach for Infrared Tracking for Soft Tissue Navigation with a Holographic Head-Mounted Display and Preclinical Validation
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Technical Approach for Infrared Tracking for Soft Tissue Navigation with a Holographic Head-Mounted Display and Preclinical Validation

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Depth-based local registration refinement for augmented reality in pituitary surgery.

Aure Enkaoua1, Manuel Villa2, João Ramalhinho3

  • 1UCL Hawkes Institute, Department of Medical Physics and Biomedical Engineering, University College London, London, UK. zcemaen@ucl.ac.uk.

International Journal of Computer Assisted Radiology and Surgery
|June 5, 2026
PubMed
Summary

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This summary is machine-generated.

Accurate augmented reality (AR) guidance in pituitary surgery requires precise 3D model registration. Depth-based refinement using monocular endoscopy significantly improves target alignment for enhanced surgical navigation.

Area of Science:

  • Neurosurgery
  • Medical Imaging
  • Computer-Aided Surgery

Background:

  • Accurate registration of pre-operative models and intra-operative endoscopic views is crucial for augmented reality (AR) guided pituitary surgery.
  • External facial reconstruction offers coarse alignment but fails to address internal anatomical motion.
  • Monocular endoscopy lacks direct depth information, complicating precise alignment at the sella region.

Purpose of the Study:

  • To develop and evaluate a depth-based refinement method for improving the accuracy of intra-operative registration in endoscopic pituitary surgery.
  • To identify a robust similarity metric for optimizing the alignment between pre-operative models and endoscopic views.

Main Methods:

  • A grid search compared monocular depth predictions from endoscopic images with pre-operative 3D model renderings.
Keywords:
Augmented RealityEndoscopic SurgeryMinimally Invasive SurgeryRegistrationTranssphenoidal Pituitary Surgery

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  • Normalized Cross-Correlation (NCC) was selected as the similarity metric for registration refinement.
  • A continuous optimization framework iteratively refined pose parameters by maximizing NCC, with periodic frame propagation for efficiency.

    • Main Results:

    • Depth-based optimization enhanced surgical target alignment, increasing DICE scores from 0.77 to 0.81 and Intersection over Union (IoU) from 0.63 to 0.68.
    • Centroid localization error was reduced by 36% through the proposed method.
    • The normalized cross-correlation metric proved robust for registration refinement.

    Conclusions:

    • The proposed depth-based refinement technique significantly improves target alignment in endoscopic AR guidance systems.
    • Monocular depth cues show considerable potential for real-time, intra-operative registration correction in surgical navigation.
    • This method enhances the reliability of AR guidance for complex procedures like pituitary surgery.