Real time magnetic resonance imaging is a promising tool for image-guided interventions. For applications such as thermatherapy on moving organs, a precise image-based compensation of motion is required in real time to allow quantitative analysis, retro-control of the interventional device, or determination of the therapy endpoint. Reduced field-of-view imaging represents a promising way to improve spatial and / or temporal resolution. However, it introduces new challenges for target motion estimation since structures near target may appear transiently due to the respiratory motion and the limited spatial coverage. In this paper, a new image based motion estimation method is proposed combining a global motion estimation with a novel optical flow approach extending the initial Horn & Schunck (H&S) method by an additional regularization term. This term integrates the displacement od physiological landmarks into the variational formulation of the optical flow problem. This allowed for a better control of the optical flow in presence of transient structures. The method was compared to the same registration pipeline employing the H&S approach on a synthetic dataset and in vivo image sequences. Compared to H&S approach, a signifiant improvment (p<0.05) of the DICE similarity criterion computed between the reference and the registered organ positions was achieved.
