Johan Juliana Dries

Model-based geometric calibration for medical x-ray systems

PURPOSE Currently applied calibration approaches lead to satisfying 3D roadmapping overlay and 3D reconstruction accuracies; however, the required calibration times are extensive. The aim of this paper is the introduction of a novel model-based approach for geometric system calibrations, leading to a significant reduction of calibration times. METHODS By using physical insight into the system, a physical model is derived which can be exploited to predict geometric calibrations parameters. Model-parameters are estimated using a limited set of phantom-based measurement data. Effectively, the calibration procedure is recast to a parameter identification experiment. RESULTS The potential of the proposed approach is illustrated by virtue of a benchmark object, successful reconstruction of a clinical phantom, and comparison to phantom-based accuracies. CONCLUSIONS Accurate models are required to achieve the desired accuracies. Based on the results in this work, the approach seems to be feasible for practical applications; however, to achieve all the desired specifications, future research should focus on enhanced modeling techniques.

Model-based approach to minimize system calibrations for 3D reconstruction quality of a cone-beam CT system

Obtaining high quality medical 3D reconstructions is of increasing importance for the medical community. The quality of a 3D reconstruction depends heavily on accurate knowledge of the position and orientation of the detector and X-ray source during a reconstruction scan. New developments in the considered class of medical imaging systems tend to lightweight design and an increasing number of scan positions. In this work, an alternative model-based approach is introduced for the currently used geometric system calibrations.