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Updated: Mar 2, 2026

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
Published on: October 27, 2023
Pose-aware C-arm for automatic re-initialization of interventional 2D/3D image registration
Javad Fotouhi1, Bernhard Fuerst2, Alex Johnson3
1Computer Aided Medical Procedures, Johns Hopkins University, Baltimore, MD, USA. fotouhi@jhu.edu.
Purpose:
In minimally invasive interventions assisted by C-arm imaging, there is a demand to fuse the intra-interventional 2D C-arm image with pre-interventional 3D patient data to enable surgical guidance. The commonly used intensity-based 2D/3D registration has a limited capture range and is sensitive to initialization. We propose to utilize an opto/X-ray C-arm system which allows to maintain the registration during intervention by automating the re-initialization for the 2D/3D image registration. Consequently, the surgical workflow is not disrupted and the interaction time for manual initialization is eliminated.
Methods:
We utilize two distinct vision-based tracking techniques to estimate the relative poses between different C-arm arrangements: (1) global tracking using fused depth information and (2) RGBD SLAM system for surgical scene tracking. A highly accurate multi-view calibration between RGBD and C-arm imaging devices is achieved using a custom-made multimodal calibration target.
Results:
Several in vitro studies are conducted on pelvic-femur phantom that is encased in gelatin and covered with drapes to simulate a clinically realistic scenario. The mean target registration errors (mTRE) for re-initialization using depth-only and RGB [Formula: see text] depth are 13.23 mm and 11.81 mm, respectively. 2D/3D registration yielded 75% success rate using this automatic re-initialization, compared to a random initialization which yielded only 23% successful registration.
Conclusion:
The pose-aware C-arm contributes to the 2D/3D registration process by globally re-initializing the relationship of C-arm image and pre-interventional CT data. This system performs inside-out tracking, is self-contained, and does not require any external tracking devices.
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