Rapid spectral analysis for spectral imaging

Steven L. Jacques; Ravikant Samatham; Niloy Choudhury

doi:10.1364/BOE.1.000157

Rapid spectral analysis for spectral imaging

Steven L. Jacques, Ravikant Samatham, Niloy Choudhury

Research output: Contribution to journal › Article › peer-review

55 Scopus citations

Abstract

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().

Original language	English (US)
Pages (from-to)	157-164
Number of pages	8
Journal	Biomedical Optics Express
Volume	1
Issue number	1
DOIs	https://doi.org/10.1364/BOE.1.000157
State	Published - Aug 2 2010
Externally published	Yes

ASJC Scopus subject areas

Biotechnology
Atomic and Molecular Physics, and Optics

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abstract = "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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AB - 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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Rapid spectral analysis for spectral imaging

Abstract

ASJC Scopus subject areas

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