{
  "id": 15772,
  "url": "https://arxiv.org/abs/2607.29337v1",
  "title": "DualDiT: A Conditional Dual-Output Diffusion Transformer for Joint OCT Image and Segmentation Mask Generation",
  "summary": "Background and Objective: Generating realistic medical images with anatomically accurate segmentation masks helps address the shortage of annotated data in medical imaging, particularly in optical coherence tomography (OCT) of mouse eyes, where manual retinal layer delineation is labour-intensive due to tiny structures and required expertise, resulting in scarce datasets. While diffusion models perform well in medical image synthesis, joint image-mask generation has relied mainly on U-Net-based",
  "authors": "Fernando García-Torres, Rocío del Amor, Sandra Morales, Álvaro Barroso, Peter Heiduschka, Björn Kemper, Valery Naranjo",
  "category": "research",
  "topics": "jobs-economy,healthcare",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-31T12:14:04.000Z",
  "fetched_at": "2026-08-03T05:10:47.622Z",
  "source_slug": "x-arxiv-cs-ai",
  "source_name": "arXiv cs.AI",
  "source_homepage": "https://arxiv.org/list/cs.AI/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/15772",
  "original_url": "https://arxiv.org/abs/2607.29337v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}