AI RESEARCH
Flexible Control of 3D CT Generation via Text and Semantically-Defined Segmentation Prompts
arXiv CS.CV
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ArXi:2606.00967v1 Announce Type: new Generative models for volumetric medical images have found many applications in medical imaging, ranging from data augmentation to serving as priors for inverse problems. For these applications, generating high-resolution 3D images with strong controllability is essential but remains highly challenging. Existing approaches typically control generation either through radiology reports used as text prompts or through full image segmentation.