Wavelet-Fusion Diffusion Model for Multimodal Brain MRI Synthesis with Modality and Metadata Conditioning
Multimodal MRI provides complementary information for neuroimaging analysis, where different imaging modalities capture distinct anatomical, tissue, and pathological features that support the development and evaluation of downstream AI applications. Although large-scale structural MRI resources are increasingly available, their modality coverage is often uneven across public and pooled neuroimaging datasets. This uneven modality coverage is further complicated by heterogeneity across sites, scanners, and acquisition protocols, as well as demographic and clinical variables that are often sparse, inconsistently recorded, or unavailable across studies. Synthetic MRI generation can help addre...
| Authors | Muhammad Nabi Yasinzai, Remika Mito, Mangor Pedersen |
|---|---|
| Primary category | cs.CV |
| Published | 30 May 2026 |
| Last updated at source | 30 May 2026 |
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