Dermal Radiomics for Melanoma Screening

Abstract

Radiomics has shown considerable promise as a new, emerging approach to computer-aided cancer screening. However, the idea of adopting radiomics for melanoma screening has not been previously explored, with clinical screening relying solely on visual assessment of skin lesion, and thus suffers from low sensitivity and specificity. In this study, a dermal radiomics framework is proposed for computer-aided screening of melanoma, with the aim of improving screening accuracy. A radiomic sequencer is designed to generate radiomic sequences consisting of 367 dermal radiomic features based on extracted physiological biomarkers from dermatological imaging data. The extracted dermal radiomic sequences were then employed to classify benign and malignant melanoma via non-linear random forest classification, and showed superior results in terms of sensitivity, specificity and accuracy when compared to the-state-of-the-art feature models for melanoma classification.