such as left ventricle (LV) depends mainly on the geometry and its motion. The geometric segmentation and reconstruction process from medical images along with the assumptions for motions of these geometries (valves and LV) can greatly influence LV’s flow pattern [@mittal2016computational; @votta2013toward; @le2013fluid]. Currently, two types of techniques are available to model the motion of valves and the LV [@doost2016heart]: 1) Fluid-Structure Interaction (FSI), and 2) prescribed models. In prescribed models, the motions and geometries are prescribed based on in vivo measurements  [@saber2003progress; @long2008subject; @schenkel2009mri] or simplified equations to define the motion [@domenichini2005three; @le2013fluid; @seo2013effect; @azar2018mechanical]. Of course, obtaining the motions from medical images is more realistic than prescribing the motion based on simplified equations. The FSI models have been widely used in numerical simulations [@watanabe2004multiphysics; @cheng2005fluid; @borazjani2008curvilinear; @borazjani2013fluid; @sharzehee2018fluid; @kamensky2015immersogeometric; @shahidian2017stress] especially for capturing the motion of heart valves. However, due to the complexity of geometry, dynamic shape, and large deformation of LV and mitral valve (MV) leaflets FSI models are computationally expensive [@borazjani2015review; @mittal2016computational], and the lack of data for tissue mechanical properties from in vivo measurements makes using them quite challenging. In fact, FSI models are typically validated by comparing the motion computed from FSI with the 