TY - JOUR
T1 - A method to detect potentially malignant skin lesions through image segmentation
AU - Wilches, Carlos A.
AU - Perdomo, Óscar J.
AU - Perdomo, César A.
N1 - Publisher Copyright:
© Springer Nature Singapore Pte Ltd. 2019.
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2019
Y1 - 2019
N2 - Melanoma is a form of skin cancer responsible for most cancer deaths. The detection of melanoma in an early stage is still a challenge with high importance. The aim of this paper was the design of a system to analyse the mole’s characteristics, based on the ABCDE criteria, for identifying potentially malignant skin lesions. The segmentation was based on Otzu thresholding, chain code and skeletonization methods were used to compute the main features: asymmetry, border, color and texture, for a future classification of skin lesions as normal or potentially malignant melanoma. The system was evaluated successfully using 92 images with 27 benign and 65 malignant melanomas from Dermatology Information System (DermIS).
AB - Melanoma is a form of skin cancer responsible for most cancer deaths. The detection of melanoma in an early stage is still a challenge with high importance. The aim of this paper was the design of a system to analyse the mole’s characteristics, based on the ABCDE criteria, for identifying potentially malignant skin lesions. The segmentation was based on Otzu thresholding, chain code and skeletonization methods were used to compute the main features: asymmetry, border, color and texture, for a future classification of skin lesions as normal or potentially malignant melanoma. The system was evaluated successfully using 92 images with 27 benign and 65 malignant melanomas from Dermatology Information System (DermIS).
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U2 - 10.1007/978-981-10-9035-6_52
DO - 10.1007/978-981-10-9035-6_52
M3 - Conference article
AN - SCOPUS:85048266565
VL - 68
SP - 289
EP - 293
JO - IFMBE Proceedings
JF - IFMBE Proceedings
SN - 1680-0737
IS - 1
T2 - World Congress on Medical Physics and Biomedical Engineering, WC 2018
Y2 - 3 June 2018 through 8 June 2018
ER -