Sigurdsson, Sigurdur1; Larsen, Jan3; Philipsen, Peter Alshede1; Gniadecka, Monika4; Wulf, Hans Christian4; Hansen, Lars Kai3
1 Department of Informatics and Mathematical Modeling, Technical University of Denmark2 Cognitive Systems, Department of Informatics and Mathematical Modeling, Technical University of Denmark3 Copenhagen Center for Health Technology, Center, Technical University of Denmark4 unknown
In this report we address the problem of skin fluorescence in feature extraction from Raman spectra of skin lesions. We apply a highly automated neural network method for suppressing skin fluorescence from Raman spectrum of skin lesions before dimension reduction with principal components analysis. By applying the background suppression, the effect of outlier spectrum in the principal components analysis was greatly reduced.