X-ray to Volume Registration

Training patient-specific 2D/3D registration models in 5 minutes

• 🚀 A single CLI/API for training models and registering clinical data
• ⚡️ 100x faster patient-specific model training than DiffPose
• 📐 Submillimeter registration accuracy with new image similarity metrics
• 🧭 Human-interpretable pose parameters for training your own models
• 🐍 Pure Python/PyTorch implementation
• 💾 Supports macOS, Linux, and Windows

Manuscript

Vivek Gopalakrishnan, Neel Dey, David-Dimitris Chlorogiannis, Andrew Abumoussa, Anna M. Larson, Darren B. Orbach, Sarah Frisken, and Polina Golland. Rapid patient-specific neural networks for intraoperative X-ray to volume registration. ArXiv (2025): arXiv-2503.