We propose a novel method by combining the total variation (TV) with the high-degree TV (HDTV) to improve the reconstruction quality of sparse-view sampling photoacoustic imaging (PAI). A weighing function is adaptively updated in an iterative way to combine the solutions of the TV and HDTV minimizations. The fast iterative shrinkage/thresholding algorithm is implemented to solve both the TV and the HDTV minimizations with better convergence rate. Numerical results demonstrate the superiority and efficiency of the proposed method on sparse-view PAI. In vitro experiments also illustrate that the method can be used in practical sparse-view PAI.

The accuracy of the background optical properties has a considerable effect on the quality of reconstructed images in near-infrared functional brain imaging based on continuous wave diffuse optical tomography (CW-DOT). We propose a region stepwise reconstruction method in CW-DOT scheme for reconstructing the background absorption and reduced scattering coefficients of the two-layered slab sample with the known geometric information. According to the relation between the thickness of the top layer and source–detector separation, the conventional measurement data are divided into two groups and are employed to recon-struct the top and bottom background optical properties, respectively. The numerical simulation results demonstrate that the proposed method can reconstruct the background optical properties of two-layered slab sample effectively. The region-of-interest reconstruction results are better than those of the conventional simultaneous reconstruction method.

Noninvasive glucose monitoring (NIGM) techniques based on optical coherence tomography (OCT) are affected by several perturbing factors, including variation of tissue temperature. We first design a temperature control module integrated with an optical scanning probe to precisely control the temperature of skin tissues. We investigate the influence of temperature on NIGM with OCT by correlation analysis at different depths of in vivo human skin. On average, the relative changes in attenuation coefficient ( μt ) per 1 °C of temperature lead to 0.30 ± 0.097 mmol/L prediction error of blood glucose concentration. For improving the accuracy of NIGM, this temperature dependence must be taken into account.