Localization of embedded inclusions using detection of fluorescence: Feasibility study based on simulation data, LS-SVM modeling and EPO pre-processing
(2008) In Chemometrics and Intelligent Laboratory Systems 91(1). p.34-42- Abstract
- Fluorescence spectroscopy is a useful technique for tissue diagnostics and is also a promising tool in the characterization of embedded structures in tissue. The emitted fluorescence from an embedded inclusion, marked with a fluorescent compound, is affected by several factors as the light propagates through the medium to the tissue boundary, where the fluorescence light is detected. Tissue absorption, scattering and autofluorescence, as well as the size and depth of the inclusion, affect the detected fluorescence light. The aim of this study is to investigate if the size and location of a fluorescent inclusion could be determined using models based a combination of External Parameter Orthogonalisation (EPO) and Least Squares Support... (More)
- Fluorescence spectroscopy is a useful technique for tissue diagnostics and is also a promising tool in the characterization of embedded structures in tissue. The emitted fluorescence from an embedded inclusion, marked with a fluorescent compound, is affected by several factors as the light propagates through the medium to the tissue boundary, where the fluorescence light is detected. Tissue absorption, scattering and autofluorescence, as well as the size and depth of the inclusion, affect the detected fluorescence light. The aim of this study is to investigate if the size and location of a fluorescent inclusion could be determined using models based a combination of External Parameter Orthogonalisation (EPO) and Least Squares Support Vector Machine (LS-SVM). This can be very useful for data pre-processing before a full fluorescence tomography reconstruction. The data set consisted of simulated multispectral fluorescence, where depth and radius of a spherical fluorescent inclusion were varied as well as the fluorescence contrast and optical properties of the surrounding tissue. The results showed that the non-linear models based on LS-SVM can simultaneously predict both radius and depth. It was observed that EPO acts as a useful pre-processing tool on spectra for this nonlinear model and that it was necessary to perform EPO to be able to predict the depth with the LS-SVM model. (C) 2007 Elsevier B.V. All rights reserved. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1207312
- author
- Chauchard, Fablen ; Svensson, Jenny LU ; Axelsson, Johan LU ; Andersson-Engels, Stefan LU and Roussel, Sylvie
- organization
- publishing date
- 2008
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- embedded, non-linearity, LS-SVM, external parameter orthogonalisation, multivariate analysis, multispectral, fluorescence spectroscopy, lesions, fluorescence tomography
- in
- Chemometrics and Intelligent Laboratory Systems
- volume
- 91
- issue
- 1
- pages
- 34 - 42
- publisher
- Elsevier
- external identifiers
-
- wos:000254819400006
- scopus:39749196097
- ISSN
- 0169-7439
- DOI
- 10.1016/j.chemolab.2007.08.008
- language
- English
- LU publication?
- yes
- id
- 3d9a78c7-f66a-48c9-9920-ea7c44b1e121 (old id 1207312)
- date added to LUP
- 2016-04-01 14:23:59
- date last changed
- 2022-03-21 23:50:41
@article{3d9a78c7-f66a-48c9-9920-ea7c44b1e121,
abstract = {{Fluorescence spectroscopy is a useful technique for tissue diagnostics and is also a promising tool in the characterization of embedded structures in tissue. The emitted fluorescence from an embedded inclusion, marked with a fluorescent compound, is affected by several factors as the light propagates through the medium to the tissue boundary, where the fluorescence light is detected. Tissue absorption, scattering and autofluorescence, as well as the size and depth of the inclusion, affect the detected fluorescence light. The aim of this study is to investigate if the size and location of a fluorescent inclusion could be determined using models based a combination of External Parameter Orthogonalisation (EPO) and Least Squares Support Vector Machine (LS-SVM). This can be very useful for data pre-processing before a full fluorescence tomography reconstruction. The data set consisted of simulated multispectral fluorescence, where depth and radius of a spherical fluorescent inclusion were varied as well as the fluorescence contrast and optical properties of the surrounding tissue. The results showed that the non-linear models based on LS-SVM can simultaneously predict both radius and depth. It was observed that EPO acts as a useful pre-processing tool on spectra for this nonlinear model and that it was necessary to perform EPO to be able to predict the depth with the LS-SVM model. (C) 2007 Elsevier B.V. All rights reserved.}},
author = {{Chauchard, Fablen and Svensson, Jenny and Axelsson, Johan and Andersson-Engels, Stefan and Roussel, Sylvie}},
issn = {{0169-7439}},
keywords = {{embedded; non-linearity; LS-SVM; external parameter orthogonalisation; multivariate analysis; multispectral; fluorescence spectroscopy; lesions; fluorescence tomography}},
language = {{eng}},
number = {{1}},
pages = {{34--42}},
publisher = {{Elsevier}},
series = {{Chemometrics and Intelligent Laboratory Systems}},
title = {{Localization of embedded inclusions using detection of fluorescence: Feasibility study based on simulation data, LS-SVM modeling and EPO pre-processing}},
url = {{https://lup.lub.lu.se/search/files/3953431/2368946.pdf}},
doi = {{10.1016/j.chemolab.2007.08.008}},
volume = {{91}},
year = {{2008}},
}