{
  "id": 494,
  "url": "https://arxiv.org/abs/2606.28980v1",
  "title": "Evidence-Based Text-Conditioned 3D CT Synthesis for Ovarian Cancer",
  "summary": "Ovarian cancer is frequently diagnosed at an advanced stage, making preoperative contrast-enhanced computed tomography (CT) central to staging and surgical planning; yet the scarcity of annotated imaging data, compounded by privacy regulations, limits the development of generalizable computational models in this domain. Text-conditioned 3D CT synthesis has shown promise, but existing pipelines depend on paired radiology reports and have been evaluated only on chest CT. We propose OvESyn (Ovarian",
  "authors": "Francesca Pia Panaccione, Eugenio Lomurno, Francesca Fati, Carlotta Pecchiari, Marina Rosanu, Luigi De Vitis et al.",
  "category": "research",
  "topics": "regulation,privacy-surveillance,healthcare",
  "orgs": null,
  "regions": null,
  "published_at": "2026-06-27T15:30:29.000Z",
  "fetched_at": "2026-07-14T14:14:32.650Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/494",
  "original_url": "https://arxiv.org/abs/2606.28980v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}