Computationally effective solution of the inverse problem in time-of-flight spectroscopy

Photon time-of-flight (PTOF) spectroscopy enables the estimation of absorption and reduced scattering coefficients of turbid media by measuring the propagation time of short light pulses through turbid medium. The present investigation provides a comparison of the assessed absorption and reduced scattering coefficients from PTOF measurements of intralipid 20% and India ink-based optical phantoms covering a wide range of optical properties relevant for biological tissues and dairy products. Three different models are used to obtain the optical properties by fitting to measured temporal profiles: the Liemert-Kienle model (LKM), the diffusion model (DM) and a white Monte-Carlo (WMC) simulation-based algorithm. For the infinite space geometry, a very good agreement is found between the LKM and WMC, while the results obtained by the DM differ, indicating that the LKM can provide accurate estimation of the optical parameters beyond the limits of the diffusion approximation in a computational effective and accurate manner. This result increases the potential range of applications for PTOF spectroscopy within industrial and biomedical applications. (C) 2015 Optical Society of Americ

Use of a single-multiple-single-mode fiber filter for interrogating fiber Bragg grating strain sensors with dynamic temperature compensation

We present a comprehensive study of the application of photon time-of-flight spectroscopy (PTOFS) in the wavelength range 1050 1350 nm as a spectroscopic technique for the evaluation of the chemical composition and structural properties of pharmaceutical tablets. PTOFS is compared to transmission near-infrared spectroscopy (NIRS). In contrast to transmission NIRS, PTOFS is capable of directly and independently determining the absorption and reduced scattering coefficients of the medium. Chemometric models were built on the evaluated absorption spectra for predicting tablet drug concentration. Results are compared to corresponding predictions built on transmission NIRS measurements. The predictive ability of PTOFS and transmission NIRS is comparable when models are based on uniformly distributed tablet sets. For non-uniform distribution of tablets based on particle sizes, the prediction ability of PTOFS is better than that of transmission NIRS. Analysis of reduced scattering spectra shows that PTOFS is able to characterize tablet microstructure and manufacturing process parameters. In contrast to the chemometric pseudovariables provided by transmission NIRS, PTOFS provides physically meaningful quantities such as scattering strength and slope of particle size. The ability of PTOFS to quantify the reduced scattering spectra, together with its robustness in predicting drug content, makes it suitable for such evaluations in the pharmaceutical industry