An Incremental Method for Registering Electroanatomic Mapping Data to Surface Mesh Models of the Left Atrium

Authors:
Aditya B. Koolwal;Federico Barbagli;Christopher R. Carlson;David H. Liang
Affiliations:
Department of Mechanical Engineering, Stanford University, USA;Department of Computer Science, Stanford University, USA and Hansen Medical, Inc., Mountain View, USA;Hansen Medical, Inc., Mountain View, USA;Division of Cardiovascular Medicine, Stanford University, USA
Venue:
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
Year:
2008

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Abstract

We present a method for registering position and orientation data collected from an electroanatomic mapping system (EMS) to a surface mesh based on segmented Computed Tomography (CT) or Magnetic Resonance (MR) images of the left atrium. Our algorithm is based on the Unscented Particle Filter (UPF) for stochastic state estimation. Using an intracardiac echo (ICE) ultrasound catheter with mounted mapping sensor, we acquire ultrasound images of the atrium from multiple configurations and iteratively determine the catheter's pose with respect to anatomy. After considering less than a minute's worth of ICE data, the algorithm converges to an accurate pose estimate which, in turn, yields the registration parameters transforming EMS coordinates to mesh coordinates. The iterative framework of the UPF allows us to be robust to unmodeled EMS noise and drift, problems which complicate traditional registration methods assuming regularity in image data structure.