MedSyn2 generates controllable high-resolution 3D CT volumes using optional text prompts and partial semantic segmentation masks via a modified diffusion transformer with gated attention.
IEEE Transactions on Biomedical Engineering73(3), 1134–1145 (2026)
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DiffSegLung distills pathology-discriminative structure from radiomic descriptors into a diffusion U-Net bottleneck for unsupervised CT lung pathology segmentation, outperforming baselines on heterogeneous cohorts.
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MedSyn2: Flexible Control of 3D CT Generation via Text and Semantically-Defined Segmentation Prompts
MedSyn2 generates controllable high-resolution 3D CT volumes using optional text prompts and partial semantic segmentation masks via a modified diffusion transformer with gated attention.
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DiffSegLung: Diffusion Radiomic Distillation for Unsupervised Lung Pathology Segmentation
DiffSegLung distills pathology-discriminative structure from radiomic descriptors into a diffusion U-Net bottleneck for unsupervised CT lung pathology segmentation, outperforming baselines on heterogeneous cohorts.