We present a framework for the registration and correspondence of magnetic resonance (MR) (three-dimensional data, 3D, data) and x-ray (two-dimensional data, 2D, data) mammographic images. The robustness of this work relies on the development of a novel method to establish nonlinear correspondence between modalities of different dimensionality, which also represent different physical tissue aspects. The correspondence is based on a 2D-2D matching process, which takes into account features from internal linear structures from both images and a measure of global similarity between modalities (Martí et al., International Journal of Pattern Recognition and Artificial Intelligence , vol. 16, no. 3, pp. 331-340, 2002). The 2D-3D correspondence relies on an intermediate step, which establishes registration between the 2D x-ray image and a projection of the 3D MR data. Initial quantitative and qualitative evaluation results, based on a small data set, are presented that show the validity of the developed approach.