Dermal Radiomics for Melanoma Screening

Daniel Cho, David Clausi, Alexander Wong

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.


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DOI: http://dx.doi.org/10.15353/vsnl.v1i1.58

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