We present further progress on the implementation of C-arm CT imaging with the extended line-ellipse-line (LEL) trajectory. This novel data acquisition geometry is designed to enhance image quality in interventional radiology. Previously, we showed that robust extended LEL data acquisition is feasible using a state-of-the-art multi-axis robotic C-arm (ARTIS pheno, Siemens Healthcare GmbH, Germany) and we also showed that accurate reconstruction from real data can be obtained using an iterative algorithm. The extensive computational effort required by such an algorithm is however not suitable for clinical translation. Reconstruction using a filtered- backprojection (FBP) formula would be practical. To use such a formula, there needs to be a technique to handle imperfections in the data acquisition geometry, which result from mechanical vibrations and gravity effects. We recently presented such a technique, but this development was only carried out for a single cycle of the LEL trajectory. In this work, we address the more challenging issue of reconstructing the volume covered by multiple cycles of the trajectory. Specifically, we propose an extension of our single cycle approach to multiple cycles. We successfully demonstrate that our procedure now allows seamless volume reconstruction from real data using a cone-beam performance phantom as well as an anthropomorphic head phantom. Our results bring the extended LEL trajectory closer to clinical deployment for improved image quality in interventional radiology. Further work will focus on increasing the number of views to avoid few view artifacts and on thoroughly demonstrating image quality benefits.
C-arm CT imaging can be improved in terms of axial coverage and cone-beam artifacts using advanced data acquisition geometries such as the extend line-ellipse-line trajectory. Previously, we showed that such a geometry can be robustly implemented on a clinical system. Here, we demonstrate that imperfections in the trajectory realization can be addressed so as to achieve accurate high contrast imaging with a theoretical-exact filtered- backprojection algorithm. The performance of the proposed algorithm is evaluated using the FORBILD head phantom as well as real data of an anthropomorphic head phantom.
Three-dimensional cone-beam (CB) imaging using a multi-axis floor-mounted (or ceiling-mounted) C-arm system has become an important tool in interventional radiology. This success motivates new developments to improve image quality. One direction in which advancement is sought is the data acquisition geometry and related CB artifacts. Currently, data acquisition is performed using the circular short-scan trajectory, which yields limited axial coverage and also provides incomplete data for accurate reconstruction. To improve the image quality, as well as to increase the coverage in the longitudinal direction of the patient, we recently introduced the ellipse- line-ellipse trajectory and showed that this trajectory provides full R-line coverage within the field-of-view, which is a key property for accurate reconstruction from truncated data. An R-line is any segment of line that connects two source positions. Here, we examine how the application of asymmetrical variations to the definition of the ELE trajectory impacts the R-line coverage. This question is significant to understand how much flexibility can be used in the implementation of the ELE trajectory, particularly to adapt the scan to patient anatomy and imaging task of interest. Two types of asymmetrical variations, called axial and angular variations, are investigated.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.