Quantitative Comparison of Color Asymmetry Features for Automatic Melanoma Detection

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Quantitative Comparison of Color Asymmetry Features for Automatic Melanoma Detection
Title:
Quantitative Comparison of Color Asymmetry Features for Automatic Melanoma Detection
Other Titles:
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Keywords:
Publication Date:
09 December 2021
Citation:
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
Abstract:
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.
License type:
Publisher Copyright
Funding Info:
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
Description:
© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
ISBN:
978-1-7281-1179-7
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