||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.