UltraTwin: Towards Cardiac Anatomical Twin Generation from Multi-view 2D Ultrasound
Journal:
arXiv
Published Date:
Jun 30, 2025
Abstract
Echocardiography is routine for cardiac examination. However, 2D ultrasound
(US) struggles with accurate metric calculation and direct observation of 3D
cardiac structures. Moreover, 3D US is limited by low resolution, small field
of view and scarce availability in practice. Constructing the cardiac
anatomical twin from 2D images is promising to provide precise treatment
planning and clinical quantification. However, it remains challenging due to
the rare paired data, complex structures, and US noises. In this study, we
introduce a novel generative framework UltraTwin, to obtain cardiac anatomical
twin from sparse multi-view 2D US. Our contribution is three-fold. First,
pioneered the construction of a real-world and high-quality dataset containing
strictly paired multi-view 2D US and CT, and pseudo-paired data. Second, we
propose a coarse-to-fine scheme to achieve hierarchical reconstruction
optimization. Last, we introduce an implicit autoencoder for topology-aware
constraints. Extensive experiments show that UltraTwin reconstructs
high-quality anatomical twins versus strong competitors. We believe it advances
anatomical twin modeling for potential applications in personalized cardiac
care.
