Authors: Pham, Tuan H.; Eker, Charlotta; Durkin, Anthony; Tromberg, Bruce J.; Andersson-Engels, Stefan

Source: Applied Spectroscopy, Volume 55, Issue 8, Pages 260A-294A and 955-1111 (August 2001) , pp. 1035-1045(11)

Publisher: Society for Applied Spectroscopy

Abstract:

A non-contact Fourier transform interferometric imaging system was used to collect hyperspectral images of the steady-state diffuse reflectance from a point source in turbid media for the spectral range of 550-850 nm. Steady-state diffuse reflectance profiles were generated from the hyperspectral images, and partial least-squares (PLS) regression was performed on the diffuse reflectance profiles to quantify absorption (μ_a) and reduced scattering (μ_s′) properties of turbid media. The feasibility of using PLS regression to predict optical properties was examined for two different sets of spatially-resolved diffuse reflectance data. One set of data was collected from 40 turbid phantoms, while the second set was generated by convolving Monte Carlo simulations with the instrument response of the imaging system. Study results show that PLS prediction of μ_a and μ_s′ was accurate to within ± 8% and ± 5%, respectively, when the model was trained on turbid phantom data. Moreover, PLS prediction of optical properties was considerably faster and more efficient than direct least-squares fitting of spatially-resolved profiles. When the PLS model was trained on Monte Carlo simulated data and subsequently used to predict μ_a and μ_s′ from the diffuse reflectance of turbid phantom, the percent accuracies degraded to ± 12% and ± 5%, respectively. These accuracy values are applicable to homogenous, semi-infinite turbid phantoms with optical property ranges comparable to tissues.

Keywords: PARTIAL LEAST SQUARES; TURBID MEDIA; DIFFUSE REFLECTANCE; OPTICAL PROPERTIES; MULTISPECTRAL IMAGING

Document Type: Research article

DOI: http://dx.doi.org/10.1366/0003702011952938

Publication date: 2001-08-01

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