Improving an affine and non-linear image registration and/or segmentation task by incorporating characteristics of the displacement field

Image registration is an important and active area of medical image processing. Given two images, the idea is to compute a reasonable displacement field which deforms one image such that it becomes similar to the other image. The design of an automatic registration scheme is a tricky task and often the computed displacement field has to be discarded, when the outcome is not satisfactory. On the other hand, however, any displacement field does contain useful information on the underlying images. It is the idea of this note, to utilize this information and to benefit from an even unsuccessful attempt for the subsequent treatment of the images. Here, we make use of typical vector analysis operators like the divergence and curl operator to identify meaningful portions of the displacement field to be used in a follow-up run. The idea is illustrated with the help of academic as well as a real life medical example. It is demonstrated on how the novel methodology may be used to substantially improve a registration result and to solve a difficult segmentation problem.