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4D(3D×T)扩散模型用于神经退行性疾病脑解剖结构的纵向生成建模。基于形变的形态测量学(DBM)和平稳速度场(SVF)。
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| name | neurodegenerative-4d-diffusion-v3 |
| description | 4D(3D×T)扩散模型用于神经退行性疾病脑解剖结构的纵向生成建模。基于形变的形态测量学(DBM)和平稳速度场(SVF)。 |
| category | ai_collection |
| source | arXiv:2604.22700 |
| published | 2026-04-24 |
| paper_url | https://arxiv.org/abs/2604.22700 |
| tags | ["neurodegenerative","4D diffusion","brain anatomy","longitudinal modeling","DBM","Alzheimer","SVF","medical imaging"] |
来源论文: Generative Modeling of Neurodegenerative Brain Anatomy with 4D Longitudinal Diffusion Model
发表日期: 2026-04-24
arXiv ID: 2604.22700
该研究提出了一种新颖的4D(3D×T)扩散生成框架，用于建模和合成随时间变化的纵向脑解剖结构。这是首个完整的4D扩散网络，能够联合学习空间和时间特征，用于神经退行性疾病（如阿尔茨海默病）的进展预测。
dφₜ/dt = v ∘ φₜ, s.t. φ₀ = x
其中v是平稳速度场，φₜ是时间t的形变场。
pip install torch torchvision
pip install nibabel # 神经影像处理
pip install monai # 医学影像深度学习
pip install numpy scipy
neurodegenerative, 4D diffusion, brain anatomy, longitudinal modeling, DBM, Alzheimer, SVF, medical imaging, disease progression