Due to its noninvasiveness, high resolution, and high sensitivity, photoacoustic imaging has developed rapidly in the field of biomedicine. However, research on dermatosis detection by photoacoustic imaging is still lacking. In this paper, the skin is modeled as a multilayer planar medium based on the non-homogeneous, complex layered structure of the skin tissue. Then, the analytical expression for the photoacoustic signal of multilayer skin tissue was derived under the assumption that the thermal and optical parameters of the skin tissue do not vary with temperature. The expression not only considers the influence of optical, thermal, and mechanical parameters of the tissue on the photoacoustic signal but also, for the first time, the influence of the number of skin layers on the photoacoustic signal. The analytical expression of the photoacoustic signal containing the number of skin layers is also given. The numerical simulation results show that the difference between the photoacoustic signal of the seven-layer skin model and the single-layer skin model is 15.206 × 10−6 MPa when ω = 3.5 MHz and μ a = 2.70 cm−1. Therefore, the increase in the number of model layers enhances the amplitude of its photoacoustic signal. This work provides a comprehensive study of photoacoustic mechanisms in dermatosis tissues and establishes a theoretical foundation for the application of photoacoustic imaging detection technology in the diagnosis and treatment of dermatosis, which may improve treatment plans.

Photoacoustic (PA) imaging technology is of some value in medical diagnoses such as breast cancer detection, vasculature imaging, and surgery navigating. While as most imaging objects are bounded, the received RF signals consist of the direct-arrived signals (DAS) from the PA sources and the boundary-reflected signals (BRS). The undesired BRS will severely impair the quality during the image reconstruction. They will bring in many artifacts and confuse the actual shape and location of the PA sources. We improved the reconstruction procedure by removing the BRS before the regular reconstruction process to suppress those artifacts. To verify our proposed method, we compared the results of the conventional and optimized procedures experimentally. In terms of qualitative observation, the reconstructed images by the optimized procedure illustrate fewer artifacts and more accurate shapes of the PA sources. To quantitatively evaluate the traditional and the optimized imaging procedure, we calculated the Distribution Relative Error (DRE) between each experiment result and its standard drawing of the phantoms. For both phantoms and the ex-vivo sample, the DREs of reconstruction result by the optimized reconstruction procedure decrease significantly. The results suggest that the optimized reconstruction process can effectively suppress the reflection artifacts and improve the shape accuracy of the PA sources.

Pinning control of cluster synchronization in a globally connected network of chaotic oscillators is studied. It is found in simulations that when the pinning strength exceeds a critical value, the oscillators are synchronized into two different clusters, one formed by the pinned oscillators and the other one formed by the unpinned oscillators. The numerical results are analyzed by the generalized method of master stability function (MSF), in which it is shown that whereas the method is able to predict the synchronization behaviors of the pinned oscillators, it fails to predict the synchronization behaviors of the unpinned oscillators. By checking the trajectories of the oscillators in the phase space, it is found that the failure is attributed to the deformed synchronization manifold of the unpinned oscillators, which is clearly deviated from that of isolated oscillator under strong pinnings. A similar phenomenon is also observed in the pinning control of cluster synchronization in a complex network of symmetric structures and in the self-organized cluster synchronization of networked neural oscillators. The findings are important complements to the generalized MSF method and provide an alternative approach to the manipulation of synchronization behaviors in complex network systems.

The development of appropriate photothermal detection of skin diseases to meet complex clinical demands is an urgent challenge for the prevention and therapy of skin cancer. An extensive body of literature has ignored all high-order harmonics above the second order and their influences on low-order harmonics. In this paper, a new iterative numerical method is developed for solving the nonlinear thermal diffusion equation to improve nonlinear photothermal detection for the noninvasive assessment of the thickness of port-wine stain (PWS). First, based on the anatomical and structural properties of skin tissue of PWS, a nonlinear theoretical model for photothermal detection is established. Second, a corresponding nonlinear thermal diffusion equation is solved by using the new iterative numerical method and taking into account harmonics above the second-order and their effects on lower-order harmonics. Finally, the thickness and excitation light intensity of PWS samples are numerically simulated. The simulation results show that the numerical solution converges fasterand the physical meaning of the solution is clearerwith the new method than with the traditional perturbation method. The rate of change in each harmonic with the sample thickness for the new method is higher than that for the conventional perturbation method, suggesting that the proposed numerical method may provide greater detection sensitivity. The results of the study provide a theoretical basis for the clinical treatment of PWS.