Published February 21, 2007 | Version v1
Journal article

Re-evaluation of pulsed photothermal radiometric profiling in samples with spectrally varied infrared absorption coefficient

  • 1. Jozef Stefan Institute, Jamova 39, SI 1000 Ljubljana (Slovenia)

Description

Spectral variation of the sample absorption coefficient in mid-infrared (μIR) demands caution in photothermal radiometric measurements, because a constant μIR is regularly assumed in inverse analysis of the acquired signals. Adverse effects of such approximation were recently demonstrated in numerical simulations of pulsed photothermal radiometric (PPTR) temperature profiling in soft biological tissues, utilizing a general-purpose optimization code in the reconstruction process. We present here an original reconstruction code, which combines a conjugate gradient minimization algorithm with non-negativity constraint to the sought temperature vector. For the same test examples as in the former report (hyper-Gaussian temperature profiles, InSb detector with 3-5 μm acquisition band, signal-to-noise ratio SNR = 300) we obtain markedly improved reconstruction results, both when using a constant value μeff and when the spectral variation μIR(λ) is accounted for in the analysis. By comparing the results, we find that the former approach introduces observable artefacts, especially in the superficial part of the profile (z < 100 μm). However, the artefacts are much less severe than previously reported and are almost absent in the case of a deeper, single-lobed test profile. We demonstrate that the observed artefacts do not result from sub-optimal selection of μeff, and that they vary with specific realizations of white noise added to the simulated signals. The same holds also for a two-lobed test profile

Additional details

Identifiers

DOI
10.1088/0031-9155/52/4/015;
PII
S0031-9155(07)31318-3;

Publishing Information

Journal Title
Physics in Medicine and Biology
Journal Volume
52
Journal Issue
4
Journal Page Range
p. 1089-1101
ISSN
0031-9155
CODEN
PHMBA7

INIS