PolyPose: Deformable 2D/3D Registration via Polyrigid Transformations
Vivek Gopalakrishnan, Neel Dey, Polina Golland

TL;DR
PolyPose introduces a polyrigid deformable registration method that efficiently aligns 3D preoperative images with sparse 2D X-ray views, leveraging biological constraints for accurate intraoperative guidance.
Contribution
It proposes a novel polyrigid formulation for 2D/3D registration that enforces anatomically plausible priors without needing complex regularizers or hyperparameter tuning.
Findings
Successfully aligns preoperative volume to two X-rays
Operates effectively in sparse-view and limited-angle scenarios
Outperforms existing registration methods in accuracy
Abstract
Determining the 3D pose of a patient from a limited set of 2D X-ray images is a critical task in interventional settings. While preoperative volumetric imaging (e.g., CT and MRI) provides precise 3D localization and visualization of anatomical targets, these modalities cannot be acquired during procedures, where fast 2D imaging (X-ray) is used instead. To integrate volumetric guidance into intraoperative procedures, we present PolyPose, a simple and robust method for deformable 2D/3D registration. PolyPose parameterizes complex 3D deformation fields as a composition of rigid transforms, leveraging the biological constraint that individual bones do not bend in typical motion. Unlike existing methods that either assume no inter-joint movement or fail outright in this under-determined setting, our polyrigid formulation enforces anatomically plausible priors that respect the piecewise-rigid…
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Code & Models
Videos
Taxonomy
TopicsModular Robots and Swarm Intelligence · Diatoms and Algae Research
MethodsALIGN · Sparse Evolutionary Training
