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Search for Resolution Invariant Wavelet Features of Melanoma Learned by a Limited ANN Classifier

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Języki publikacji
EN
Abstrakty
EN
This article addresses the Computer Aided Diagnosis (CAD) of melanoma pigmented skin cancer. We present back-propagated Artificial Neural Network (ANN) classifiers discriminating dermoscopic skin lesion images into two classes: malignant melanoma and dysplastic nevus. Features used for our classification experiments are derived from wavelet decomposition coefficients of the image. Our research objective is i) to select the most efficient topology of the hidden layers and the network learning algorithm for full-size and downgraded image resolutions and, ii) to search for resolution-invariant topologies and learning methods. The analyzed classifiers should be fit to work on ARM-based hand-held devices, hence we take into account only limited learning setups.
Słowa kluczowe
EN
melanoma   CAD   wavelets   ANN  
Rocznik
Tom
Strony
189--207
Opis fizyczny
Bibliogr. 67 poz., rys.
Twórcy
autor
  • Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, 30-151 Kraków, Poland
  • Institute of Technology, State Higher Vocational School, 33-300 Nowy Sącz, Poland
Bibliografia
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Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-c36e5cf1-e8c6-474a-afa2-b7407c26c3c1
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