A fast slam approach to freehand 3-d ultrasound reconstruction for catheter ablation guidance in the left atrium.

We present a method for real-time, freehand 3D ultrasound (3D-US) reconstruction of moving anatomy, with specific application towards guiding the catheter ablation procedure in the left atrium. Using an intracardiac echo (ICE) catheter with a pose (position/orientation) sensor mounted to its tip, we continually mosaic 2D-ICE images of a left atrium phantom model to form a 3D-US volume. Our mosaicing strategy employs a probabilistic framework based on simultaneous localization and mapping (SLAM), a technique commonly used in mobile robotics for creating maps of unexplored environments.

A probabilistic framework for freehand 3D ultrasound reconstruction applied to catheter ablation guidance in the left atrium.

Introduction: The catheter ablation procedure is a minimally invasive surgery used to treat atrial fibrillation. Difficulty visualizing the catheter inside the left atrium anatomy has led to lengthy procedure times and limited success rates. In this paper, we present a set of algorithms for reconstructing 3D ultrasound data of the left atrium in real-time, with an emphasis on automatic tissue classification for improved clarity surrounding regions of interest.

Catheter localization in the left atrium using an outdated anatomic reference for guidance.

We present a method for registering real-time ultrasound of the left atrium to an outdated, anatomic surface mesh model, whose shape differs from that of the anatomy. Using an intracardiac echo (ICE) catheter with mounted 6DOF electromagnetic position/orientation sensor (EPS), we acquire images of the left atrium and determine where the ICE catheter must be positioned relative to the surface mesh to generate similar, "virtual" ICE images. Further, we use an affine warping model to infer how the shape of the surface mesh differs from that of the atrium.

An incremental method for registering electroanatomic mapping data to surface mesh models of the left atrium.

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.