2094 3D visualization of active catheters using compressed sensing
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Meeting abstract
2094 3D visualization of active catheters using compressed sensing Carsten O Schirra*1, Sascha Krueger2, Steffen Weiss2, Reza Razavi1, Tobias Schaeffter1 and Sebastian Kozerke3 Address: 1King's College London, Interdisciplinary Medical Imaging Group, Division of Imaging Sciences, London, UK, 2Philips Research Europe, Medical Imaging Systems, Hamburg, Germany and 3University and ETH Zurich, Institute for Biomedical Engineering, Zurich, Switzerland * Corresponding author
from 11th Annual SCMR Scientific Sessions Los Angeles, CA, USA. 1–3 February 2008 Published: 22 October 2008 Journal of Cardiovascular Magnetic Resonance 2008, 10(Suppl 1):A363
doi:10.1186/1532-429X-10-S1-A363
Abstracts of the 11th Annual SCMR Scientific Sessions - 2008
Meeting abstracts – A single PDF containing all abstracts in this Supplement is available here. http://www.biomedcentral.com/content/pdf/1532-429X-10-S1-info.pdfThis abstract is available from: http://jcmr-online.com/content/10/S1/A363 © 2008 Schirra et al; licensee BioMed Central Ltd.
Introduction A crucial requirement in MR-guided interventions is the visualization of catheter devices in real-time. Common tracking techniques rely either on image projections to localize the catheter tip [1] or on single slice imaging [2] to capture the extent of the catheter in parts. True threedimensional visualisation of the full length of catheter devices has hitherto been impossible given scan time constraints. Compressed Sensing (CS) has recently been proposed as a method to accelerate MR imaging of sparse objects [3]. Since most objects to be imaged are not sparse in the image domain itself, a suitable transform basis is to be found permitting application of the CS method. Active catheters are sparse objects per se and therefore are well suited to the CS framework without requiring any further sparsifying transformation. It is the objective of this work to investigate the feasibility and the limits of CS for visualizing active catheters in three dimensions while satisfying real-time conditions.
Materials and methods Data acquisition A high-resolution image volume of the heart and the aorta (resolution 1 mm3) was acquired on a 1.5 T Philips Achieva system (Fig. 1a) using a 5 element cardiac coil (Philips Medical Systems, Best, The Netherlands). A virtual catheter consisting of a single loop antenna (length 100 mm) was simulated and positioned inside the aorta (Fig. 1b). Sensitivity values of the active device were calculated using Biot-Savart's law. The sensitivity values were multiplied with the in-vivo data to yield a virtual simula-
tion environment based on realistic in-vivo anatomy (Fig. 1c). In CS, scan acceleration is achieved by random undersampling the phase-encode dimensions (Fig. 1d). In this work, the density of random undersampling was varied according to a Gaussian probability function with higher sampling density at the centre of k-space for net undersampling factors ranging from 2 – 80. Data reconstruction Randomly u
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