Toward Video-Based Navigation for Endoscopic Endonasal Skull Base Surgery

Authors:
Daniel Mirota;Hanzi Wang;Russell H. Taylor;Masaru Ishii;Gregory D. Hager
Affiliations:
Department of Computer Science, The Johns Hopkins University, Baltimore, USA;School of Computer Science, The University of Adelaide, Australia;Department of Computer Science, The Johns Hopkins University, Baltimore, USA;Department of Otolaryngology, Johns Hopkins Medical Institutions, Baltimore, USA;Department of Computer Science, The Johns Hopkins University, Baltimore, USA
Venue:
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part I
Year:
2009

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Abstract

Endoscopic endonasal skull base surgery (ESBS) requires high accuracy to ensure safe navigation of the critical anatomy at the anterior skull base. Current navigation systems provide approximately 2mm accuracy. This level of registration error is due in part from the indirect nature of tracking used. We propose a method to directly track the position of the endoscope using video data. Our method first reconstructs image feature points from video in 3D, and then registers the reconstructed point cloud to pre-operative data (e.g. CT/MRI). After the initial registration, the system tracks image features and maintains the 2D-3D correspondence of image features and 3D locations. These data are then used to update the current camera pose. We present registration results within 1mm, which matches the accuracy of our validation framework.