The use of long-axis images in cardiac MRI segmentation is essential in order to locate the valves and delineate the ventriclesa?? volume accurately. However, depending on the imaging protocol used, long-axis images do not always provide enough support for straightforward segmentation. We show that it is possible to use both short-axis and long-axis images for segmentation, even in cases where the long-axis images do not cover the entire heart volume and have various orientations and spacings, and different gains and contrasts. We propose a method to achieve this goal, based on the simultaneous interpolation and segmentation of the data in a level set framework. Results on both synthetic and real images are presented.