ArticleMedical physics2024
Fully automatic online geometric calibration for non-circular cone-beam CT orbits using fiducials with unknown placement.
Article in Medical physics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed, 6 citations in OpenAlex.
- Differentiable Forward and Back-Projector for Rigid Motion Estimation in X-Ray Imaging.IEEE transactions on bio-medical engineering · 2026Article
- Phantom-Free Geometric Refinement for Industrial CBCT Using Physical Constraints and a Normalized Low-Rank Projection Prior.Sensors (Basel, Switzerland) · 2026Article
- Forward and Back Projectors for Gradient-based Rigid Motion Estimation in X-ray Imaging.Proceedings of SPIE--the International Society for Optical Engineering · 2026Article
- Joint Cone-Beam CT Reconstruction and Rigid Motion Compensation Using A Differentiable Projector.Proceedings of SPIE--the International Society for Optical Engineering · 2026Article
- RoboCT: The State and Current Challenges of Industrial Twin Robotic CT Systems.Sensors (Basel, Switzerland) · 2025Review
- Universal non-circular cone beam CT orbits for metal artifact reduction imaging during image-guided procedures.Scientific reports · 2024Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 3 countries.
Funding
Abstract
backgroundCone-beam CT (CBCT) with non-circular scanning orbits can improve image quality for 3D intraoperative image guidance. However, geometric calibration of such scans can be challenging. Existing methods typically require a prior image, specialized phantoms, presumed repeatable orbits, or long computation time. PURPOSE: We propose a novel fully automatic online geometric calibration algorithm that does not require prior knowledge of fiducial configuration. The algorithm is fast, accurate, and can accommodate arbitrary scanning orbits and fiducial configurations.
methodsThe algorithm uses an automatic initialization process to eliminate human intervention in fiducial localization and an iterative refinement process to ensure robustness and accuracy. We provide a detailed explanation and implementation of the proposed algorithm. Physical experiments on a lab test bench and a clinical robotic C-arm scanner were conducted to evaluate spatial resolution performance and robustness under realistic constraints.
resultsQualitative and quantitative results from the physical experiments demonstrate high accuracy, efficiency, and robustness of the proposed method. The spatial resolution performance matched that of our existing benchmark method, which used a 3D-2D registration-based geometric calibration algorithm.
conclusionsWe have demonstrated an automatic online geometric calibration method that delivers high spatial resolution and robustness performance. This methodology enables arbitrary scan trajectories and should facilitate translation of such acquisition methods in a clinical setting.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.