Using Gabor filter banks and temporal-spatial constraints to compute 3D myocardium strain.

In this paper, we describe a new approach for reconstructing 3D strains in the myocardium using tagged MR images. We first segment the myocardium using a 3D deformable model driven by image gradients and Gabor filter responses. Tags are automatically detected and tracked as deformable thin plates during systole and early diastole. To keep the tracking results more stable and consistent, we use a combination of gradient information, an intensity probabilistic model, the phase information, and a temporal-spatial smoothness constraint. Based on the tag deformation, we compute a dense displacement in the myocardium around both ventricles. The displacements in x-, y-, and z- directions are calculated separately and are combined to form the final displacement maps. We do not use the information outside the segmented surface of the myocardium to avoid displacement errors caused by noises, artifacts, and correlations between different regions in the myocardium. The strain in the myocardium during the heart cycle is derived from the displacement. This method accepts images of either a tag grid or separate horizontal and vertical tag lines as its input. Experimental results on phantom and real data demonstrate good performance of this method in calculating the myocardial strain.