| In this paper we present a new approach for the registration of two
cardiac 4D image sequences. In a first step we establish a temporal association
between the sequences. For one (or two) selected pair(s) of associated points in
time of both sequences, which we call the bridging points in time, we allow the use
of additional information such as the semi-automatic segmentation of the
investigated structure. We establish the 3D inter-subject registration for each other
pair of associated points in time exploiting (1) the inter-subject registration for the
bridging pair of points in time, (2) the intra-subject motion calculation in both
sequences between the currently considered points in time and the bridging pair,
and (3) the concatenation of the obtained transformations. We formulate a cost
functional integrating the similarity measures comparing the images of the bridging
pair(s) of points in time and of the current pair of points in time, respectively. We
evaluated our algorithm on 8 healthy volunteers leading to 28 intersubject
combinations and we analyze the behaviour for different parameter settings
weighting differently the involved pairs of points in time. The approach based on the bridging pairs outperforms a direct 3D registration of corresponding points in
time, in particular in the right ventricle we gain up to 33% in registration accuracy.
Starting with a cost functional taking into account the similarity at the first bridging
point in time, the results improve stepwise by integrating, additionally, first,
information from the current pair of points in time and secondly, from a second
bridging point in time. Finally, we show an example visualizing, for different pairs
of initial points in time, a comparison of the motion fields of two subjects. |