Markerless Registration and Visualization of Volumetric Medical Data for Enhanced Surgical Precision Using Head-Mounted Displays

In surgery, accurate localization of critical structures like blood vessels is crucial, yet current 2D visualization methods limit precision and increase cognitive load for surgeons. This paper introduces a markerless registration approach that uses only sensors in a Head-Mounted Display to align CT/MRI data directly onto the patient in a 3D space. Point clouds extracted from CT/MRI data are registered with world captures from the Head-Mounted Display’s time-of-flight camera, allowing for precise visualization. We evaluated the system using physical measurements on phantoms and compared algorithmic registration to manual alignment. The results show a registration error of approx. 4.87±0.05mm, demonstrating the potential of this technique for preoperative planning and intraoperative support.

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Publication Details

Published
2025-03-08
DOI
https://doi.org/10.1109/vrw66409.2025.00189
Citations
1
Primary Topic
Surgical Simulation and Training
Type
article
Field-Weighted Citation Impact
2.01
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article

Markerless Registration and Visualization of Volumetric Medical Data for Enhanced Surgical Precision Using Head-Mounted Displays

Artur Jurgas, Andrzej Skalski, Maciej Stanuch, Michał Trojak
1 citations
Surgical Simulation and Training
2.01
article

Markerless Registration and Visualization of Volumetric Medical Data for Enhanced Surgical Precision Using Head-Mounted Displays

Artur Jurgas, Andrzej Skalski, Maciej Stanuch, Michał Trojak
article en
1 citations

Abstract

In surgery, accurate localization of critical structures like blood vessels is crucial, yet current 2D visualization methods limit precision and increase cognitive load for surgeons. This paper introduces a markerless registration approach that uses only sensors in a Head-Mounted Display to align CT/MRI data directly onto the patient in a 3D space. Point clouds extracted from CT/MRI data are registered with world captures from the Head-Mounted Display’s time-of-flight camera, allowing for precise visualization. We evaluated the system using physical measurements on phantoms and compared algorithmic registration to manual alignment. The results show a registration error of approx. 4.87±0.05mm, demonstrating the potential of this technique for preoperative planning and intraoperative support.

Jagiellonian University (PL), NetApp (United States) (US), AGH University of Krakow (PL)
Openalex Percentile: Top 17%
Surgical Simulation and Training
2.01
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