Optimization of Spatial Frequency Domain Imaging Technique for Estimating Optical Properties of Food and Biological Materials

Abstract. Spatial frequency domain imaging technique has recently been developed for determination of the optical properties of food and biological materials. However, accurate estimation of the optical property parameters by the technique is challenging due to measurement errors associated with signal acquisitions and the complex inverse parameter estimation algorithm for the diffusion model. This research was therefore aimed at optimizing the inverse algorithm for estimating the optical absorption (μ_a) and reduced scattering (μ_s^′) coefficients from spatial frequency domain diffuse reflectance generated by Monte Carlo simulation. Sensitivity analysis was first conducted, and it showed that μ_s^′ could be estimated more accurately than μ_a. Six data smoothing methods were then compared, with the results indicating that the ‘moving‘ method with a span of 5 data points was the most effective in improving the parameter estimation. Further studies were conducted to determine the optimal frequency resolution and start and end frequencies in terms of the reciprocal of mean free path (1/mfp‘). The results showed that the optimal frequency resolution increased with μ_s^′ and remained stable when μ_s^′ was larger than 2 mm^-1. The optimal end frequency decreased from 0.3/mfp‘ to 0.16/mfp‘ with μ_s^′ ranging from 0.4 mm^-1 to 3 mm^-1, while the optimal start frequency remained at 0 mm^-1. A two-step method was proposed based on the optimized frequency parameters, which improved estimation accuracies by 37.5% and 9.8% for μ_a and μ_s^′, respectively, compared with the conventional method. Experimental validation with seven liquid optical phantoms showed that the optimized technique resulted in the mean absolute errors of 15.4%, 7.6%, 5.0% for μ_a and 16.4%, 18.0%, 18.3% for μ_s^′ at the wavelengths of 675 nm, 700 nm, and 715 nm, respectively. Hence, implementation of the optimized technique can result in better measurement of optical properties of food and agricultural products.