Guo Z (2025)
Publication Language: English
Publication Type: Thesis
Publication year: 2025
URI: https://doi.org/10.25593/open-fau-2269
DOI: https://open.fau.de/handle/openfau/37339
Three-dimensional cone-beam (CB) imaging using multi-axis (fixed, floor- or ceiling-mounted) angiographic C-arm systems has become a valuable tool in interventional radiology. This technology is referred to as C-arm computed tomography (CT). C-arm CT is capable of offering real-time fluoroscopic guidance and CT-like imaging. The valuable information provided by C-arm CT benefits both in diagnosis and complicated treatment. The performance of C-arm CT in clinics, however, usually suffers from incomplete data acquisition in terms of Tuy’s condition, and improper handling of data redundancy in image reconstruction. These, as a result, limit the capability of C-arm CT to yield exact reconstruction, and lead to degraded image quality with CB artifacts. Besides, the current data acquisition trajectory only provides a limited field-of-view (FOV). This results in truncation problems when scanning long anatomical sites. In this dissertation, I explore the property of the Line-Ellipse-Line (LEL) data acquisition trajectory and modify it to an extended version–this modified version is referred to as the extended LEL trajectory. This novel trajectory is able to provide complete data acquisition so that stable and theoretically exact reconstruction is achievable, meanwhile providing more flexibility on data selection in coping with data redundancy. Based on the geometrical design of the trajectory, an adapted filtered back-projection reconstruction algorithm is devised, which turns out to have a comparable detector utilization with the conventional circular short-scan. Moreover, the extended LEL trajectory is capable to offer a broadened FOV by the means of continuously repeating its trajectory segments. This feature can be used to further benefit image quality with reduced scatter in a manner of applying narrow axial beam collimation. This dissertation covers a series of discussions including parametric description of the trajectory geometry, the formulae and implementation details of the analytical reconstruction algorithm, the evaluations on both noise-free and noisy images with computer simulated data, the performance of the first implementation of this trajectory on a state-of-the-art robotic C-arm system, the problem encountered in real data acquisition and its management strategy, as well as the imaging performance using those real data experiments. Promising results are obtained from both computer simulations and real data, which make the extended LEL trajectory a good prospect for clinical translation.
APA:
Guo, Z. (2025). Computed Tomography using the Extended Line-Ellipse-Line Trajectory on a Robotic C-arm System (Dissertation).
MLA:
Guo, Zijia. Computed Tomography using the Extended Line-Ellipse-Line Trajectory on a Robotic C-arm System. Dissertation, 2025.
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