SurgNavAR: An Augmented Reality Surgical Navigation Framework for Optical See-Through Head Mounted Displays
2026-03-31 • Computer Vision and Pattern Recognition
Computer Vision and Pattern Recognition
AI summaryⓘ
The authors created and tested a system that uses special glasses to help surgeons see important medical images directly on a patient during surgery. Their system can track tools and the patient, align images with the body, and work in real time. They checked how well it worked in two different surgeries using practice models and found it to be accurate within a few millimeters. The system is designed to be easy to use, adaptable to different surgeries, and is freely available online.
augmented realityhead mounted displaysurgical navigationimage-to-patient registrationtool calibrationHoloLens 2Magic Leap 2needle insertionrib fracture localization
Authors
Abdullah Thabit, Mohamed Benmahdjoub, Rafiuddin Jinabade, Hizirwan S. Salim, Marie-Lise C. van Veelen, Mark G. van Vledder, Eppo B. Wolvius, Theo van Walsum
Abstract
Augmented reality (AR) devices with head mounted displays (HMDs) facilitate the direct superimposition of 3D preoperative imaging data onto the patient during surgery. To use an HMD-AR device as a stand-alone surgical navigation system, the device should be able to locate the patient and surgical instruments, align preoperative imaging data with the patient, and visualize navigation data in real time during surgery. Whereas some of the technologies required for this are known, integration in such devices is cumbersome and requires specific knowledge and expertise, hampering scientific progress in this field. This work therefore aims to present and evaluate an integrated HMD-based AR surgical navigation framework that is adaptable to diverse surgical applications. The framework tracks 2D patterns as reference markers attached to the patient and surgical instruments. It allows for the calibration of surgical tools using pivot and reference-based calibration techniques. It enables image-to-patient registration using point-based matching and manual positioning. The integrated functionalities of the framework are evaluated on two HMD devices, the HoloLens 2 and Magic Leap 2, with two surgical use cases being evaluated in a phantom setup: AR-guided needle insertion and rib fracture localization. The framework was able to achieve a mean tooltip calibration accuracy of 1 mm, a registration accuracy of 3 mm, and a targeting accuracy below 5 mm on the two surgical use cases. The framework presents an easy-to-use configurable tool for HMD-based AR surgical navigation, which can be extended and adapted to many surgical applications. The framework is publicly available at https://github.com/abdullahthabit/SurgNavAR.