Rapid spectral analysis for spectral imaging

Spectral imaging requires rapid analysis of spectra associated with each pixel. A rapid algorithm has been developed that uses iterative matrix inversions to solve for the absorption spectra of a tissue using a lookup table for photon pathlength based on numerical simulations. The algorithm uses tis...

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Detalles Bibliográficos
Autores principales: Jacques, Steven L., Samatham, Ravikant, Choudhury, Niloy
Formato: Texto
Lenguaje:English
Publicado: Optical Society of America 2010
Materias:
Optics of Tissue and Turbid Media
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3005184/
https://www.ncbi.nlm.nih.gov/pubmed/21258455
http://dx.doi.org/10.1364/BOE.1.000157
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author Jacques, Steven L.
Samatham, Ravikant
Choudhury, Niloy
author_facet Jacques, Steven L.
Samatham, Ravikant
Choudhury, Niloy
author_sort Jacques, Steven L.
collection PubMed
description Spectral imaging requires rapid analysis of spectra associated with each pixel. A rapid algorithm has been developed that uses iterative matrix inversions to solve for the absorption spectra of a tissue using a lookup table for photon pathlength based on numerical simulations. The algorithm uses tissue water content as an internal standard to specify the strength of optical scattering. An experimental example is presented on the spectroscopy of portwine stain lesions. When implemented in MATLAB, the method is ~100-fold faster than using fminsearch().
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spelling pubmed-30051842011-01-21 Rapid spectral analysis for spectral imaging Jacques, Steven L. Samatham, Ravikant Choudhury, Niloy Biomed Opt Express Optics of Tissue and Turbid Media Spectral imaging requires rapid analysis of spectra associated with each pixel. A rapid algorithm has been developed that uses iterative matrix inversions to solve for the absorption spectra of a tissue using a lookup table for photon pathlength based on numerical simulations. The algorithm uses tissue water content as an internal standard to specify the strength of optical scattering. An experimental example is presented on the spectroscopy of portwine stain lesions. When implemented in MATLAB, the method is ~100-fold faster than using fminsearch(). Optical Society of America 2010-07-15 /pmc/articles/PMC3005184/ /pubmed/21258455 http://dx.doi.org/10.1364/BOE.1.000157 Text en ©2010 Optical Society of America http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 Unported License, which permits download and redistribution, provided that the original work is properly cited. This license restricts the article from being modified or used commercially.
spellingShingle Optics of Tissue and Turbid Media
Jacques, Steven L.
Samatham, Ravikant
Choudhury, Niloy
Rapid spectral analysis for spectral imaging
title Rapid spectral analysis for spectral imaging
title_full Rapid spectral analysis for spectral imaging
title_fullStr Rapid spectral analysis for spectral imaging
title_full_unstemmed Rapid spectral analysis for spectral imaging
title_short Rapid spectral analysis for spectral imaging
title_sort rapid spectral analysis for spectral imaging
topic Optics of Tissue and Turbid Media
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3005184/
https://www.ncbi.nlm.nih.gov/pubmed/21258455
http://dx.doi.org/10.1364/BOE.1.000157
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AT samathamravikant rapidspectralanalysisforspectralimaging
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