Deep Learning-based Point Cloud Registration for Augmented Reality-guided Surgery
arxiv(2024)
摘要
Point cloud registration aligns 3D point clouds using spatial
transformations. It is an important task in computer vision, with applications
in areas such as augmented reality (AR) and medical imaging. This work explores
the intersection of two research trends: the integration of AR into
image-guided surgery and the use of deep learning for point cloud registration.
The main objective is to evaluate the feasibility of applying deep
learning-based point cloud registration methods for image-to-patient
registration in augmented reality-guided surgery. We created a dataset of point
clouds from medical imaging and corresponding point clouds captured with a
popular AR device, the HoloLens 2. We evaluate three well-established deep
learning models in registering these data pairs. While we find that some deep
learning methods show promise, we show that a conventional registration
pipeline still outperforms them on our challenging dataset.
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