Erythema and hyperpigmentation delineation for cutaneous chronic graft-versus-host disease using hyperspectral reconstruction

Erythema body surface area is a key indicator of cutaneous chronic graft-versus-host disease (cGVHD) status, but clinician estimation is unreliable and confounded by hyperpigmentation. Existing automated methods either fit predictive algorithms to subjective human annotations or require costly hyperspectral imagers. To our knowledge, we present the first annotation-free method to delineate both erythema and hyperpigmentation from standard RGB images. Our pipeline (i) reconstructs hyperspectral images from RGB input and (ii) unmixes these into hemoglobin and melanin abundance maps, which predict erythema and hyperpigmentation, respectively. Trained only on synthetic images, the method achieved a median binary classification accuracy above 0.70 across both conditions and both synthetic images and clinical photographs, demonstrating generalizability to the clinical environment.