mlsanityData to 7 Oct 2026

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

arXiv 1903.09339 ↗First posted 22 Mar 2019cs.CV eess.IVcited by 10

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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.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Mar 2019.

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Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 0; 2025: 5; 2026: 2.

10 papers.