Whole-heart 3D CSPAMM allows for fast and reliable functional imaging of the beating heart by mapping the deformation of magnetization patterns throughout the left ventricle and cardiac cycle [1]. Its clinical use has been limited mainly due to (i) the time-consuming post-processing of tagged MR images, and (ii) derivation of clinically relevant biomarkers from the data. Regarding the post-processing of tagged MR images, multiple approaches have been proposed [2]; however, some of these methods are computationally expensive and consensus about a preferred algorithm is still lacking. Regarding clinically relevant prognostic information, biomechanical models are increasingly considered as a potential tool to characterize patient condition and predict patient outcome through the integration of patient-specific data including ventricular strain [3]–[5]; however, the integration of finite element biomechanical models and image data remains challenging. The objective of the present work was to develop, validate and analyze a finite element digital image correlation tool to extract ventricular strain data from MR images, which can be applied to both 3D CSPAMM images and conventional multi-slice cine images.