DualDiT: A Conditional Dual-Output Diffusion Transformer for Joint OCT Image and Segmentation Mask Generation
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
Record details
Published: 31 July 2026
Source: arXiv cs.AI
Category: Research
Topics: Jobs & economy · Healthcare
Retrieved: 3 August 2026
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ethics.ai (31 July 2026), “DualDiT: A Conditional Dual-Output Diffusion Transformer for Joint OCT Image and Segmentation Mask Generation,” evidence record 15772, https://ethics.ai/record/15772 (originally published by arXiv cs.AI).
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