Estimating and suppressing background in Raman spectra with an artificial neural network

Sigurdur Sigurdsson; Jan Larsen; Peter Alshede Philipsen; Monika Gniadecka; Hans Christian Wulf; Lars Kai Hansen

Estimating and suppressing background in Raman spectra with an artificial neural network

Sigurdur Sigurdsson, Jan Larsen, Peter Alshede Philipsen, Monika Gniadecka, Hans Christian Wulf, Lars Kai Hansen

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Abstract

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.

Original language	English

Publication status	Published - 2003

Access to Document

Imm2839

http://www.imm.dtu.dk/pubdb/p.php?2839

Cite this

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title = "Estimating and suppressing background in Raman spectra with an artificial neural network",

abstract = "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.",

author = "Sigurdur Sigurdsson and Jan Larsen and Philipsen, {Peter Alshede} and Monika Gniadecka and Wulf, {Hans Christian} and Hansen, {Lars Kai}",

year = "2003",

language = "English",

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TY - RPRT

T1 - Estimating and suppressing background in Raman spectra with an artificial neural network

AU - Sigurdsson, Sigurdur

AU - Larsen, Jan

AU - Philipsen, Peter Alshede

AU - Gniadecka, Monika

AU - Wulf, Hans Christian

AU - Hansen, Lars Kai

PY - 2003

Y1 - 2003

N2 - 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.

AB - 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.

M3 - Report

BT - Estimating and suppressing background in Raman spectra with an artificial neural network

ER -