标题： UltraTwin：从多视图2D超声波走向心脏解剖双生体生成 显示英文标题

标题： UltraTwin: Towards Cardiac Anatomical Twin Generation from Multi-view 2D Ultrasound

摘要： 超声心动图是心脏检查的常规方法。 然而，二维超声（US）在准确的度量计算和直接观察三维心脏结构方面存在困难。 此外，三维超声受低分辨率、小视野和实际应用中稀缺性的限制。 从二维图像构建心脏解剖双胞胎有望提供精确的治疗计划和临床量化。 然而，由于配对数据稀少、结构复杂和超声噪声，这仍然具有挑战性。 在本研究中，我们引入了一种新颖的生成框架UltraTwin，以从稀疏的多视角二维US获取心脏解剖双胞胎。 我们的贡献有三个方面。 首先，开创性地构建了一个包含严格配对的多视角二维US和CT以及伪配对数据的真实世界高质量数据集。 其次，我们提出了一种从粗到细的方案，以实现分层重建优化。 最后，我们引入了一个隐式自编码器以实现拓扑感知约束。 大量实验表明，UltraTwin相对于强大的竞争对手能够重建高质量的解剖双胞胎。 我们认为，它推动了解剖双胞胎建模的发展，有望应用于个性化的心脏护理。 显示英文摘要

摘要： 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.