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In non-rigid image registration there are some distinct outliers introduced by the insertion or removal of some image contents, abrupt intensity changes, and local non-smooth deformations in the two images to register. Recently, non-rigid registration of images with outliers has received a great deal of attention in medical imaging research. This work presents a framework for robust non-rigid registration based on the theory of optical flow, within which we use outlier detection to implement locally-refined control point setup in multilevel free- form deformation (FFD) model. We also introduce robust M-estimator to weaken the effect of outliers in global optimization to get improved registration result. We have successfully applied our proposed method to a number of registration tasks to demonstrate its applicability and robustness to outliers.