| In this paper we present a new approach for the registration of cardiac 4D image sequences of different subjects,
where we assume that a temporal association between the sequences is given. Moreover, we allow for one (or two)
selected pair(s) of associated points in time of both sequences, which we call the bridging points in time, the use
of additional information such as the semi-automatic segmentation of the investigated structure. We establish
the 3D inter-subject registration for all other pairs of 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 with respect
to 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
inter-subject 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, firstly, information from the current pair of points in time and secondly, from
a second bridging point in time. Our results also show a steep rise of the importance of regularization on the
registration accuracy when registering the current point in time with our procedure (17% gain in accuracy) with
respect to a direct registration in the bridging point (less than 1%). However, regularization during intra-sequence
registration had only minor effects on the accuracy of our registration procedure. |