Genetic Programming for Multiple Feature Construction in Skin Cancer Image Classification
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gp-bibliography.bib Revision:1.7964
- @InProceedings{UlAin:2019:IVCNZ,
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author = "Qurrat {Ul Ain} and Bing Xue and Harith Al-Sahaf and
Mengjie Zhang",
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booktitle = "2019 International Conference on Image and Vision
Computing New Zealand (IVCNZ)",
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title = "Genetic Programming for Multiple Feature Construction
in Skin Cancer Image Classification",
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year = "2019",
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month = dec,
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1109/IVCNZ48456.2019.8961001",
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ISSN = "2151-2205",
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abstract = "Skin cancer is a common cancer worldwide, with
melanoma being the most deadly form which is treatable
when diagnosed at an early stage. This study develops a
novel classification approach using multi-tree genetic
programming (GP), which not only targets melanoma
detection but is also capable of distinguishing between
ten different classes of skin cancer effectively from
lesion images. Selecting a suitable feature extraction
method and the way different types of features are
combined are important aspects to achieve performance
gains. Existing approaches remain unable to effectively
design a way to combine various features. Moreover,
they have not used multi-channel multi-resolution
spatial/frequency information for effective feature
construction. In this work, wavelet-based texture
features from multiple color channels are employed
which preserve all the local, global, color and texture
information concurrently. Local Binary Pattern, lesion
color variation, and geometrical border shape features
are also extracted from various color channels. The
performance of the proposed method is evaluated using
two skin image datasets and compared with an existing
multi-tree GP method, ten single-tree GP methods, and
six commonly used classification algorithms. The
results reveal the goodness of the proposed method
which significantly outperformed all these
classification methods and demonstrate the potential to
help dermatologist in making a diagnosis in real-time
situations.",
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notes = "Also known as \cite{8961001}",
- }
Genetic Programming entries for
Qurrat Ul Ain
Bing Xue
Harith Al-Sahaf
Mengjie Zhang
Citations