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Titlebook: Deep Generative Models; 4th MICCAI Workshop, Anirban Mukhopadhyay,Ilkay Oksuz,Yixuan Yuan Conference proceedings 2025 The Editor(s) (if app

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61#
發(fā)表于 2025-4-1 02:54:29 | 只看該作者
,WDM: 3D Wavelet Diffusion Models for?High-Resolution Medical Image Synthesis,Ns, Diffusion Models, and Latent Diffusion Models. Our proposed method is the only one capable?of consistently generating high-quality images at a resolution of ., outperforming all comparing methods.?The project page is available?at ..
62#
發(fā)表于 2025-4-1 06:54:24 | 只看該作者
,Energy-Based Prior Latent Space Diffusion Model for?Reconstruction of?Lumbar Vertebrae from?Thick Sigh-quality?image generation. Crucially, we mitigate their high computational cost?and low sample efficiency by learning an energy-based latent representation to perform the diffusion processes. Our resulting method outperforms existing approaches across metrics including?Dice and VS scores, and mor
63#
發(fā)表于 2025-4-1 13:31:27 | 只看該作者
,Anatomically-Guided Inpainting for?Local Synthesis of?Normal Chest Radiographs,contextual attention inpainting network (CAttNet), an anatomically-guided inpainting network (AnaCAttNet) is proposed that leverages anatomical information of the original CXR through segmentation to guide the inpainting for a more realistic reconstruction. A quantitative evaluation of the inpaintin
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