Dual Fluoroscopy Imaging BACKGROUND
the derived IOPs vary from one image to another, which is incorrect for a stationary DF system.
Lichti et al. 2015 proposed a rigorous procedure for the calibration of DF systems. Their approach is based on
performing bundle adjustment with self-calibration. By simultaneously using redundant measurements of calibration
targets in convergent images, it was shown that the solution for the IOPs and ROPs through the bundle adjustment is precise,
unique, and straightforward. Nevertheless, to allow for such a bundle adjustment solution, the imaged targets must be
manually digitized, spatially measured and then related to their 3D object space homologues. Due to the absence of
coloursemantic information in the DF images, a substantial amount of manual work was needed to prepare the input data
for bundle adjustment. The transmissive nature of an X-ray-based imaging approach
leads to ambiguous image scenes that are not common in optical photogrammetry. For instance, the calibration targets at
different depths may overlap one another. In addition, the targets have no semanticcoded information, which complicates
the task of automating the calibration process. This research introduces a framework to facilitate the calibration of DF
imaging systems. The paper begins with a review of relevant literature regarding the applications of DF imaging systems and
their common calibration approaches. Section 2 provides a brief background on the DF imaging process and summarizes the
theoretical bases of the calibration approach proposed by Lichti et al. 2015. Section 3 explains the proposed methodology for
the extraction, localization and identification of the calibration targets. The proposed methodology is then evaluated in the
results section through a calibration experiment Section 4. Finally, the paper presents relevant conclusions and
recommendations for future work Section 5.