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Vision-Guided Surgical Navigation Using Computer Vision for Dynamic Intraoperative Imaging Updates.

Jeremy Ruthberg1, Nicole Gunderson2, Pengcheng Chen2

  • 1Department of Otolaryngology-Head and Neck Surgery, University of Washington, Seattle, Washington, USA.

International Forum of Allergy & Rhinology
|August 23, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method using neural radiance fields (NeRF) to create real-time 3D surgical field reconstructions from endoscopic video, improving accuracy in endoscopic sinus surgery (ESS). The technique enables dynamic intraoperative imaging for enhanced surgical completeness.

Keywords:
3D reconstructionartificial intelligencechronic sinusitiscomputer‐assisted surgerydeep learningimage‐guided surgery

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Area of Science:

  • Medical Imaging
  • Computer Vision
  • Surgical Technology

Background:

  • Residual disease after endoscopic sinus surgery (ESS) leads to poor outcomes and repeat surgeries.
  • Current image-guided surgery systems lack dynamic intraoperative updates.
  • A sensorless, video-based method using neural radiance fields (NeRF) for intraoperative CT updating is proposed.

Purpose of the Study:

  • To develop and validate a novel method for dynamic intraoperative CT updating using NeRF.
  • To assess the accuracy of NeRF-generated 3D surgical field reconstructions compared to preoperative CT scans.
  • To evaluate the potential of this technology to improve surgical completeness in ESS.

Main Methods:

  • Bilateral ESS was performed on 3D-printed models.
  • Endoscopic videos were processed using a custom NeRF pipeline for 3D reconstruction.
  • NeRF reconstructions were co-registered to preoperative CT scans, and updated CT models were generated and compared to ground-truth postoperative CT using Hausdorff distance, DSC, and BAA.

Main Results:

  • Sub-millimeter surface alignment was achieved with an average Hausdorff distance of 0.27 ± 0.076 mm.
  • Excellent volumetric overlap was demonstrated with a Dice Similarity Coefficient (DSC) of 0.93 ± 0.012.
  • Bland-Altman analysis showed acceptable volume agreement, with a mean difference of 0.40 cm³.

Conclusions:

  • Computer vision, specifically NeRF, enables accurate, dynamic intraoperative CT updates from endoscopic video without external tracking.
  • This software-driven tool visualizes resection progress, potentially enhancing surgical completeness in ESS.
  • The technology offers a pathway for next-generation surgical navigation platforms.