{
  "id": 575,
  "url": "https://arxiv.org/abs/2606.26764v1",
  "title": "Anatomy-Guided Residual Motion Diffusion for Controllable 4D Cardiac MRI Synthesis",
  "summary": "Developing robust artificial intelligence models for 4D (3D + time) medical imaging is constrained by limited annotated data, inter-device domain shifts, and privacy restrictions. To address this, we propose a 4D controllable generative framework for anatomically consistent data augmentation. A semi-supervised variational autoencoder learns a compact latent representation of anatomical volumes while jointly predicting aligned segmentation masks in a unified framework. Anatomical structure is the",
  "authors": "Yiheng Cao, Gustavo Andrade-Miranda, Jiatian Zhang, Lingxiao Zhao, Xin Gao",
  "category": "research",
  "topics": "privacy-surveillance,healthcare",
  "orgs": null,
  "regions": null,
  "published_at": "2026-06-25T08:48:45.000Z",
  "fetched_at": "2026-07-14T14:14:37.249Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/575",
  "original_url": "https://arxiv.org/abs/2606.26764v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}