Independent component analysis applied to raman spectra for classification of in vitro human coronary arteries
Contribuinte(s) |
UNIVERSIDADE DE SÃO PAULO |
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Data(s) |
19/10/2012
19/10/2012
2008
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Resumo |
Optical diagnostic methods, such as near-infrared Raman spectroscopy allow quantification and evaluation of human affecting diseases, which could be useful in identifying and diagnosing atherosclerosis in coronary arteries. The goal of the present work is to apply Independent Component Analysis (ICA) for data reduction and feature extraction of Raman spectra and to perform the Mahalanobis distance for group classification according to histopathology, obtaining feasible diagnostic information to detect atheromatous plaque. An 830nm Ti:sapphire laser pumped by an argon laser provides near-infrared excitation. A spectrograph disperses light scattered from arterial tissues over a liquid-nitrogen cooled CCD to detect the Raman spectra. A total of 111 spectra from arterial fragments were utilized. |
Identificador |
INSTRUMENTATION SCIENCE & TECHNOLOGY, v.36, n.2, p.134-145, 2008 1073-9149 http://producao.usp.br/handle/BDPI/22718 10.1080/10739140701850845 |
Idioma(s) |
eng |
Publicador |
TAYLOR & FRANCIS INC |
Relação |
Instrumentation Science & Technology |
Direitos |
restrictedAccess Copyright TAYLOR & FRANCIS INC |
Palavras-Chave | #Raman spectroscopy #Independent Component Analysis (ICA) #Mahalanobis distance #human coronary artery #MAHALANOBIS DISTANCE #SOURCE SEPARATION #ANALYSIS ICA #ATHEROSCLEROSIS #SPECTROSCOPY #SIGNALS #Chemistry, Analytical #Instruments & Instrumentation |
Tipo |
article original article publishedVersion |