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Accelerated 3D catheter visualization from triplanar MR projection images
Authors:Carsten Oliver Schirra  Steffen Weiss  Sascha Krueger  Denis Caulfield  Steen F. Pedersen  Reza Razavi  Sebastian Kozerke  Tobias Schaeffter
Affiliation:1. King's College London, Division of Imaging Sciences, London, UK;2. Philips Research Europe, Hamburg, Germany;3. University Hospital Arhus, Skejby, Denmark;4. Institute for Biomedical Engineering, University of Zurich and Swiss Federal Institute of Technology, Zurich, Switzerland
Abstract:One major obstacle for MR‐guided catheterizations is long acquisition times associated with visualizing interventional devices. Therefore, most techniques presented hitherto rely on single‐plane imaging to visualize the catheter. Recently, accelerated three‐dimensional (3D) imaging based on compressed sensing has been proposed to reduce acquisition times. However, frame rates with this technique remain low, and the 3D reconstruction problem yields a considerable computational load. In X‐ray angiography, it is well understood that the shape of interventional devices can be derived in 3D space from a limited number of projection images. In this work, this fact is exploited to develop a method for 3D visualization of active catheters from multiplanar two‐dimensional (2D) projection MR images. This is favorable to 3D MRI as the overall number of acquired profiles, and consequently the acquisition time, is reduced. To further reduce measurement times, compressed sensing is employed. Furthermore, a novel single‐channel catheter design is presented that combines a solenoidal tip coil in series with a single‐loop antenna, enabling simultaneous tip tracking and shape visualization. The tracked tip and catheter properties provide constraints for compressed sensing reconstruction and subsequent 2D/3D curve fitting. The feasibility of the method is demonstrated in phantoms and in an in vivo pig experiment. Magn Reson Med, 2010. © 2010 Wiley‐Liss, Inc.
Keywords:interventional MRI  active catheters  projection imaging  compressed sensing
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