Real-time motion estimation is challenging, especially with MR imaging where an intrinsic tradeoff exists between spatial and temporal resolution. The spatially varying pharmacokinetic behavior of contrast agents contributes to intensity inhomogeneity and contrast changing, introducing a further obstacle in motion estimation. In this study, we propose a novel level set based motion estimation method based on the observation that higher order geometric features present in anatomic boundaries are less influenced by contrast and intensity inhomogeneity due to low SNR and/or contrast changes. More specifically, our method first estimates the movement of anatomical boundaries, and then extrapolates them to the whole domain of interest. Preliminary tests have demonstrated desirable error statistics on MR images with simulated contrast and intensity inhomogeneity, as would be the case when contrast agents are used. Tests based on real-time MR image sequences have revealed visually appealing results, conforming to prior physical and physiological understanding.