Myocardial deformation from tagged MRI in hypertrophic cardiomyopathy using an efficient registration strategy

This paper combines different parallelization strategies for speeding up motion and deformation computation by non-rigid registration of a sequence of images. The registration is performed in a two-level acceleration approach: (1) parallelization of each registration process using MPI and/or threads, and (2) distribution of the sequential registrations over a cluster. On a 24-node double quad-core Intel Xeon (2.66 GHz CPU, 16 GB RAM) cluster, the method is demonstrated to efficiently compute the deformation of a cardiac sequence reducing the computation time from more than 3 hours to a couple of minutes (for low downsampled images). It is shown that the distribution of the sequential registrations over the cluster together with the parallelization of each pairwise registration by multithreading lowers the computation time towards values compatible with clinical requirements (a few minutes per patient). The combination of MPI and multithreading is only advantageous for large input data sizes. Performances are assessed for the specific scenario of aligning cardiac sequences of taggedMagnetic Resonance (tMR) images, with the aim of comparing strain in healthy subjects and hypertrophic cardiomyopathy (HCM) patients. In particular, we compared the distribution of systolic strain in both populations. On average, HCM patients showed lower average values of strain with larger deviation due to the coexistence of regions with impaired deformation and regions with normal deformation.