An Automatic Registration Approach for Ventricle Insertion Navigation Using the HoloLens2

Abstract

The application of Augmented Reality (AR) technology in neurosurgery is becoming increas- ingly widespread, especially in External Ventricular Drainage (EVD) procedures, where achiev- ing efficient and precise registration remains a key challenge. Traditional marker-based registra- tion methods are often complex and time-consuming, making them unsuitable for emergency surgical situations. This paper presents a markerless automatic registration method based on HoloLens 2, using the Dlib library to automatically detect facial landmarks, and perform- ing point cloud registration based on these features. We designed four sets of experiments: first, to verify the feasibility of the triangle-based registration algorithm; second, to assess the accuracy and stability of Dlib’s feature point extraction on HoloLens; third, to validate the registration accuracy, including the impact of skin displacement; and finally, to evaluate the accuracy of the insertion path in a simulated EVD procedure. The experimental results show that this method simplifies the registration process and demonstrates advantages in terms of registration accuracy and speed, effectively meeting the real-time and precision requirements of emergency surgeries. This study provides an efficient and reliable AR navigation solution for EVD procedures, with promising prospects for further research.