Multiview 2D/3D image registration in minimally invasive pelvic surgery navigation.

ABSTRACT: 2D/3D medical image registration is crucial for image-guided surgery and medical research. Single-view methods often lack depth information, while multiview approaches typically rely on large-scale training datasets, which may not always be available in clinical scenarios. This paper explores the feasibility of multiview registration with insufficient data. We propose an innovative multiview 2D/3D image registration model with three key components: a points of interest (POIs) tracking network based on style transfer (POITT), a triangulation layer, and shape alignment based on branch and bound (SA-BnB). POITT constructs a POIs tracking network on Digital Reconstructed Radiographs images (DRRs) and performs points matching on X-ray images via style transfer. The triangulation layer establish

SUBMITTER: Ju F 

PROVIDER: S-EPMC12274519 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature