Patient-level hyperspectral state-space learning for melanoma pathology diagnosis

Background

Histopathologic differentiation of cutaneous melanoma from pigmented nevus can be difficult when morphology is subtle. Microscopic hyperspectral imaging records tissue in contiguous narrow spectral bands across the visible and near-infrared range and may provide quantitative optical information beyond routine bright-field microscopy. We developed MelanoSpec-SSM, a patient-level spectral-spatial state-space algorithm for label-free hyperspectral pathology diagnosis.