J Kim*, H Zhong, Henry Ford Hospital System, Detroit, MI
TH-A-211-2 Thursday 8:00:00 AM - 8:55:00 AM Room: 211
Deformable image registration algorithms generally consist of three components, similarity metric, transformation, and optimization. In addition to these components, the optimization also includes one or more regularization terms such as the smoothness of the underlying deformation or restrictions based on the physical properties of organs. It is also common for most of the algorithms to take a multi-resolution approach to capture large initial deformations as well as to speed up the registration process. Understanding and proper choice of such parameters are critical to a successful registration. The effects of different choices of parameters will be presented using public domain algorithms as well as commercial software.
Learning objectives: 1) To understand the basic constituents of deformable image registration algorithms. 2) To understand the consequences of the different parameter choices.