Foundation VAEs for 3D CT Reconstruction, Augmentation, and Generation 事件

Foundation VAEs for 3D CT Reconstruction, Augmentation, and Generation arXiv:2605.30893v1 Announce Type: new Abstract: Variational autoencoders (VAEs) compress high resolution CT volumes into compact latents while preserving clinically relevant structure. However, training CT-specific VAEs from scratch or heavily fine-tuning them incurs substantial computational and engineering cost, and often degrades under heterogeneous scanners, protocols, and diseases. This paper makes a progressive stride