# Pose Estimation of Periacetabular Osteotomy Fragments with Intraoperative X-Ray Navigation

arXiv: https://arxiv.org/abs/1903.09339 · HTML: https://mlsanity.com/paper/1903.09339/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Mar 2019.

## Built on by (most cited first, 10 of 10)

- [Intraoperative 2D/3D Image Registration via Differentiable X-ray Rendering](https://mlsanity.com/paper/2312.06358/) (2023)
- [The Impact of Machine Learning on 2D/3D Registration for Image-guided Interventions: A Systematic Review and Perspective](https://mlsanity.com/paper/2108.02238/) (2021)
- [SyntheX: Scaling Up Learning-based X-ray Image Analysis Through In Silico Experiments](https://mlsanity.com/paper/2206.06127/) (2022)
- [Benchmark of Segmentation Techniques for Pelvic Fracture in CT and X-ray: Summary of the PENGWIN 2024 Challenge](https://mlsanity.com/paper/2504.02382/) (2025)
- [PolyPose: Deformable 2D/3D Registration via Polyrigid Transformations](https://mlsanity.com/paper/2505.19256/) (2025)
- [Automatic Multi-View X-Ray/CT Registration Using Bone Substructure Contours](https://mlsanity.com/paper/2506.13292/) (2025)
- [Rapid patient-specific neural networks for intraoperative X-ray to volume registration](https://mlsanity.com/paper/2503.16309/) (2025)
- [Robust and Accurate Multi-view 2D/3D Image Registration with Differentiable X-ray Rendering and Dual Cross-view Constraints](https://mlsanity.com/paper/2506.22191/) (2025)
- [X-GuideAR: An Augmented Reality Framework to Mitigate Radiation Exposure during Fluoroscopic Guidance](https://mlsanity.com/paper/2607.10873/) (2026)
- [FleXray: Universal Clinical X-ray Segmentation](https://mlsanity.com/paper/2609.26756/) (2026)

## Abstract (arXiv)

Objective: State of the art navigation systems for pelvic osteotomies use optical systems with external fiducials. We propose the use of X-Ray navigation for pose estimation of periacetabular fragments without fiducials. Methods: A 2D/3D registration pipeline was developed to recover fragment pose. This pipeline was tested through an extensive simulation study and 6 cadaveric surgeries. Using osteotomy boundaries in the fluoroscopic images, the preoperative plan is refined to more accurately match the intraoperative shape. Results: In simulation, average fragment pose errors were 1.3deg/1.7 mm when the planned fragment matched the intraoperative fragment, 2.2deg/2.1 mm when the plan was not updated to match the true shape, and 1.9deg/2.0 mm when the fragment shape was intraoperatively estimated. In cadaver experiments, the average pose errors were 2.2deg/2.2 mm, 3.8deg/2.5 mm, and 3.5deg/2.2 mm when registering with the actual fragment shape, a preoperative plan, and an intraoperatively refined plan, respectively. Average errors of the lateral center edge angle were less than 2deg for all fragment shapes in simulation and cadaver experiments. Conclusion: The proposed pipeline is capable of accurately reporting femoral head coverage within a range clinically identified for long-term joint survivability. Significance: Human interpretation of fragment pose is challenging and usually restricted to rotation about a single anatomical axis. The proposed pipeline provides an intraoperative estimate of rigid pose with respect to all anatomical axes, is compatible with minimally invasive incisions, and has no dependence on external fiducials.