Abstract
Magnetic resonance imaging (MRI) inpainting supports numerous clinical and research applications. We introduce the first generative model that conditions on voxel-level, continuous tumor concentrations to synthesize high-fidelity brain tumor MRIs. For the BraTS 2025 Inpainting Challenge, we adapt this architecture to the complementary task of healthy tissue restoration by setting the tumor concentrations to zero. Our latent diffusion model conditioned on both tissue segmentations and the tumor concentrations generates 3D spatially coherent and anatomically consistent images for both tumor synthesis and healthy tissue inpainting. For healthy inpainting, we achieve a PSNR of 18.5, and for tumor inpainting, we achieve 17.4. Our code is available at: this https URL
Abstract (translated)
磁共振成像（MRI）的修复技术支持众多临床和研究应用。我们介绍了首个生成模型，该模型以体素级别的、连续的肿瘤浓度为条件，合成高质量的大脑肿瘤MRI图像。对于BraTS 2025补全挑战赛，我们将此架构调整用于健康的组织恢复任务，方法是将肿瘤浓度设为零。我们的潜在扩散模型在同时考虑组织分割和肿瘤浓度的情况下，能够生成具有空间连贯性和解剖学一致性的3D图像，适用于肿瘤合成及健康组织修复。对于健康组织的修复，我们达到了18.5的PSNR值；而对于肿瘤修复，则达到17.4的PSNR值。我们的代码可在以下网址获取：[this https URL]
URL
https://arxiv.org/abs/2510.09365
