A crucial requirement in MR-guided interventions is the visualization of catheter devices in real time. However, true 3D visualization of the full length of catheters 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. Images acquired with active interventional devices exhibit a high CNR and are inherently sparse, therefore rendering CS ideally suited for accelerating data acquisition.
A framework for true visualization of active catheters
in 3D is proposed employing CS to gain high undersampling
factors making real-time applications feasible. Constraints are introduced taking into account prior knowledge of catheter geometry and catheter motion over time to improve and accelerate image reconstruction. The potential of the method is demonstrated using computer simulations and phantom experiments and in vivo feasibility is demonstrated in a pig experiment.