Particle swarm optimization for in vivo 3D ultrasound volume registration

As three-dimensional (3D) ultrasound is becoming more and more popular, there has been increased interest in using a position sensor to track the trajectory of the 3D ultrasound probe during the scan. One application is the improvement of image quality by fusion of multiple scans from different orientations. With a position sensor mounted on the probe, the clinicians face additional difficulties, for example, maintaining a line-of-sight between the sensor and the reference point. Therefore, the objective of this paper is to register the volumes using an automatic image-based registration technique. In this paper, we employ the particle swarm optimization (PSO) technique to calculate the six rigid-body transformation parameters (three for translation and three for rotation) between successive volumes of 3D ultrasound data. We obtain vertical and horizontal slices through the acquired volumes and then use an intensity-based similarity measure as a fitness function for each particle. We considered various settings in the PSO to find a set of parameters to give the best convergence. We found the visually acceptable registration when the initial orientations of the particles were confined to within a few degrees of the orientations obtained from position sensor