Myocardial fiber orientations are an important element for accurate modeling of cardiac electromechanics. However it is extremely difficult to estimate these directly in vivo with current imaging techniques. Most current methods for cardiac modeling use synthetic models of fiber orientation which may fail to capture subtle variations of fiber orientations in different hearts. We present a method to map the fiber orientations obtained from diffusion tensors from a template onto patientspecific cardiac geometry, using elastic registration followed by a reorientation of the diffusion tensors based on the local rotation component of the transformation. The effectiveness of the diffusion tensor mapping is validated on a set of diffusion tensor imaging datasets obtained from 19 canine subjects. The algorithm was able to map the diffusion tensors effectively for both healthy and failing hearts.