Clinical Graph-Mediated Distillation for Unpaired MRI-to-CFI Hypertension Prediction
Retinal fundus imaging enables low-cost and scalable hypertension (HTN) screening, but HTN-related retinal cues are subtle, yielding high-variance predictions. Brain MRI provides stronger vascular and small-vessel-disease markers of HTN, yet it is expensive and rarely acquired alongside fundus images, resulting in modality-siloed datasets with disjoint MRI and fundus cohorts. We study this unpaired MRI-fundus regime and introduce Clinical Graph-Mediated Distillation (CGMD), a framework that transfers MRI-derived HTN knowledge to a fundus model without paired multimodal data. CGMD leverages shared structured biomarkers as a bridge by constructing a clinical similarity kNN graph spanning bo...
| Authors | Dillan Imans, Phuoc-Nguyen Bui, Duc-Tai Le et al. |
|---|---|
| Primary category | cs.CV |
| Published | 23 March 2026 |
| Last updated at source | 29 July 2026 |
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