Abstract
We apply filter-based image classification methods to skin lesion images obtained by two different recording systems. The task is to distinguish different malignant and benign diseases. This is done by extracting features form fluorescence images by applying adaptively learnt or predefined filters and applying a standard classification algorithm to the filter outputs. Several methods for filter bank creation such as ICA, PCA, NMF and Gabor filters are compared.
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Stockmeier, H.G., Bäcker, H., Bäumler, W., Lang, E.W. (2009). BSS-Based Feature Extraction for Skin Lesion Image Classification. In: Adali, T., Jutten, C., Romano, J.M.T., Barros, A.K. (eds) Independent Component Analysis and Signal Separation. ICA 2009. Lecture Notes in Computer Science, vol 5441. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00599-2_59
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DOI: https://doi.org/10.1007/978-3-642-00599-2_59
Publisher Name: Springer, Berlin, Heidelberg
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