Genetic programming for skin cancer detection in dermoscopic images
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{ain:2017:CEC,
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author = "Qurrat {Ul Ain} and Bing Xue and Harith Al-Sahaf and
Mengjie Zhang",
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booktitle = "2017 IEEE Congress on Evolutionary Computation (CEC)",
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title = "Genetic programming for skin cancer detection in
dermoscopic images",
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year = "2017",
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editor = "Jose A. Lozano",
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pages = "2420--2427",
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address = "Donostia, San Sebastian, Spain",
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publisher = "IEEE",
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isbn13 = "978-1-5090-4601-0",
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abstract = "Development of an effective skin cancer detection
system can greatly assist the dermatologist while
significantly increasing the survival rate of the
patient. To deal with melanoma detection, knowledge of
dermatology can be combined with computer vision
techniques to evolve better solutions. Image
classification can significantly help in diagnosing the
disease by accurately identifying the morphological
structures of skin lesions responsible for developing
cancer. Genetic Programming (GP), an emerging
Evolutionary Computation technique, has the potential
to evolve better solutions for image classification
problems compared to many existing methods. In this
paper, GP has been used to automatically evolve a
classifier for skin cancer detection and also analysed
GP as a feature selection method. For combining
knowledge of dermatology and computer vision
techniques, GP has been given domain specific features
provided by the dermatologists as well as Local Binary
Pattern features extracted from the dermoscopic images.
The results have shown that GP has significantly
outperformed or achieved comparable performance
compared to the existing methods for skin cancer
detection.",
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keywords = "genetic algorithms, genetic programming, cancer,
computer vision, feature selection, image
classification, medical image processing, patient
diagnosis, GP, computer vision techniques, dermoscopic
images, disease diagnosis, domain specific features,
evolutionary computation technique, feature selection
method, local binary pattern features, melanoma
detection, patient survival rate, skin cancer
detection, Feature extraction, Image color analysis,
Malignant tumors, Mutual information, Sensitivity,
Skin, Skin cancer",
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isbn13 = "978-1-5090-4601-0",
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DOI = "doi:10.1109/CEC.2017.7969598",
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month = "5-8 " # jun,
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notes = "IEEE Catalog Number: CFP17ICE-ART Also known as
\cite{7969598}",
- }
Genetic Programming entries for
Qurrat Ul Ain
Bing Xue
Harith Al-Sahaf
Mengjie Zhang
Citations