A Communication Term for the Combined Registration and Segmentation
Accurate image registration is a necessary prerequisite for many diagnostic and therapy planning procedures where complementary information from different images has to be combined. The design of robust and reliable non-parametric registration schemes is currently a very active research area. Modern approaches combine the pure registration scheme with other image processing routines such that both ingredients may benefit from each other. One of the new approaches is the combination of segmentation and registration (“segistration”). Here, the segmentation part guides the registration to its desired configuration, whereas on the other hand the registration leads to an automatic segmentation. By joining these image processing methods it is possible to overcome some of the pitfalls of the individual methods. Here, we focus on the benefits for the registration task.
To combine segmentation and registration, a special communication or coupling term is needed. In this note we present a novel coupling term, which overcomes the pitfalls of conventional ones. It turned out that not only the achieved results were better, but the overall scheme converges much faster, resulting in a favorable computation time.
The performance tests were carried out for magnetic resonance (MR) images of the brain demonstrating the striking the potential of the proposed method for real live examples.
Keywordssegistration medical image registration segmentation mathematical modeling magnet resonance imaging neuro-imaging
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