Motivation: In prostate brachytherapy, real-time dosimetry would be ideal to allow for rapid evaluation of the implant
quality intra-operatively. However, such a mechanism requires an imaging system that is both real-time and which
provides, via multiple C-arm fluoroscopy images, clear information describing the three-dimensional position of the
seeds deposited within the prostate. Thus, accurate tracking of the C-arm poses proves to be of critical importance to the
process. Methodology: We compute the pose of the C-arm relative to a stationary radiographic fiducial of known
geometry by employing a hybrid registration framework. Firstly, by means of an ellipse segmentation algorithm and a
2D/3D feature based registration, we exploit known FTRAC geometry to recover an initial estimate of the C-arm pose.
Using this estimate, we then initialize the intensity-based registration which serves to recover a refined and accurate
estimation of the C-arm pose. Results: Ground-truth pose was established for each C-arm image through a published and
clinically tested segmentation-based method. Using 169 clinical C-arm images and a ±10° and ±10 mm random
perturbation of the ground-truth pose, the average rotation and translation errors were 0.68° (std = 0.06°) and 0.64 mm
(std = 0.24 mm). Conclusion: Fully automated C-arm pose estimation using a 2D/3D hybrid registration scheme was
found to be clinically robust based on human patient data.