Srivastava, R., Ong, E. P., Lee, B.-H., Tan, L. S., & Liang Tey, H. (2021). Quantitative Comparison of Color Asymmetry Features for Automatic Melanoma Detection. 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). doi:10.1109/embc46164.2021.9631103
Asymmetry assessment is an important step
towards melanoma detection. This paper compares some of
the color asymmetry features proposed in the literature which
have been used to automatically detect melanoma from color
images. A total of nine features were evaluated based on
their accuracy in predicting lesion asymmetry on a dataset
of 277 images. In addition, the accuracies of these features in
differentiating melanoma from benign lesions were compared.
Results show that simple features based on the brightness
difference between the two halves of the lesion performed the
best in predicting asymmetry and subsequently melanoma.
Clinical relevance— The proposed work will assist researchers
in choosing better performing color asymmetry features
thereby improving the accuracy of automatic melanoma
detection. The resulting system will reduce the workload of
clinicians by screening out obviously benign cases and referring
only the suspicious cases to them.
This research / project is supported by the National Skin Centre, National Healthcare Group - Centre for Medical Technologies and Innovations (CMTi) and National Health Innovation Centre Singapore (NHIC) Joint MedTech
Grant Reference no. : CMTi-NHIC/19009