Joint Myocardial Motion and Contraction Phase Estimation from Cine MRI Using Variational Data Assimilation
Résumé
We present a cardiac motion estimation method with variational data assimilation that combines image observations and a dynamic
evolution model. The novelty of the model is that it embeds new parameters modeling heart contraction and relaxation. It was applied to a
synthetic dataset with known ground truth motion and to 10 cine-MRI sequences of patients with normal or dyskinetic myocardial zones. It
was compared to the inTag tagging tracking software for computing the radial motion component, and to the diagnosis for dyskinesia. We found
that the new dynamic model performed better than the standard transport model, and the contraction parameters are promising features for
diagnosing dyskinesia.