Towards estimating cardiac motion using low-rank representation and topology preservation for ultrafast ultrasound data

Estimation of the cardiac motion is very important in order to detect heart diseases. This work presents a cardiac motion estimation approach using ultrafast ultrasound data. We optimize a variational framework which has the benefits of combining low-rank data representation with topology preservation. We show through the analysis of experimental results that this combination offers a radical reduction in computational time and noise while ensuring preservation of the anatomical structure of the heart under complex deformations. Although in this work we use the heart as a study case, our solution is promising to analyze other organs experiencing motion.