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Automating the ABCD Rule for Melanoma Detection: A Survey

Ali A, Li J & Yang G (2020) Automating the ABCD Rule for Melanoma Detection: A Survey. IEEE Access, 8, pp. 83333-83346.

The ABCD rule is a simple framework that physicians, novice dermatologists and non-physicians can use to learn about the features of melanoma in its early curable stage, enhancing thereby the early detection of melanoma. Since the interpretation of the ABCD rule traits is subjective, different solutions have been proposed in literature to tackle such subjectivity and provide objective evaluations to the different traits. This paper reviews the main contributions in literature towards automating asymmetry, border irregularity, color variegation and diameter, where the different methods involved have been highlighted. This survey could serve as an essential reference for researchers interested in automating the ABCD rule.

Image processing; machine learning; melanoma detection

IEEE Access: Volume 8

Author(s)Ali, Abder-Rahman; Li, Jingpeng; Yang, Guang
Publication date31/12/2020
Publication date online30/04/2020
Date accepted by journal25/04/2020
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
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