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We developed a method to reconstruct the 3D dense motion field of the left ventricle (LV) over one cardiac cycle from a fusion of cine and tagged cardiovascular magnetic resonance (CMR) images. The inputs to our methods are (i) a set of short-axis (SA) and long-axis (LA) tagged CMR images of the LV over one cardiac cycle, and (ii) a set of border-delineated cine CMR images of the LV at end-diastole. A hexahedral mesh of the LV myocardium is reconstructed from the border-delineated cine images and used for the dense motion field reconstruction. First, 2D in-plane deformations from both the SA and LA tagged images are computed using the Harmonic Phase (HARP) data analysis tool. These 2D in-plane deformations are then mapped onto the hexahedral mesh to produce a sparse 3D motion field on the mesh as inter-slice deformations are not available. Next, a finite-element method (FEM) model is used to compute the inter-slice deformations. The sparse 3D motion field from SA and LA tagged images is imposed as prescribed boundary conditions in the FEM model, and the unknown inter-slice deformations are solved for each frame in the cardiac cycle. The novelty of our approach is the combination of both sets of in-plane deformations from the SA and LA tagged images, which yields more accurate motion quantification as opposed to using solely the SA or LA. Furthermore, compared to the conventional interpolation approach, our method produces a 3D dense motion field that is physiologically relevant and prevents displacement of adjacent points from intersecting.

Reconstruction of 3D Dense Cardiac Motion Field from Cine and Tagged Magnetic Resonance Images