arXiv: cs.AI preprintsInternational6 November 2026
A latent ODE approach to full-cycle biventricular cardiac motion modeling from cine MRI
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arXiv:2606.26718v2 Announce Type: replace Abstract: Cardiac magnetic resonance imaging (CMR) captures rich spatiotemporal information about ventricular structure and motion, but conventional risk models use only a few image-derived indices from selected cardiac phases. We present a latent dynamical model that encodes bi-ventricular anatomy and full-cycle cine motion as a continuous latent trajectory, using heart-rate-aware neural ordinary differential equation (ODE) dynamics and a graph-based mesh autoencoder to reconstruct anatomically consistent 3D+t ventricular motion. A covariate-condition
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