Extended global optimization strategy for rigid 2D/3D image registration

Rigid 2D/3D image registration is a common strategy in medical image processing. In this paper we present an extended global optimization strategy for a rigid 2D/3D image registration that consists of three components: a combination of a global and a local optimizer, a combination of a multi-scale and a multi-resolution approach, and a combination of an in-plane and an out-of-plane registration. The global optimizer Adaptive Random Search is used to provide several coarse registration results on a low resolution level that are refined by the local optimizer Best Neighbor on a higher resolution level. We evaluate the performance and the precision of our registration algorithm using two phantom models. We could approve that all three components of our optimization strategy lead to an significant improvement of the registration.