Data-driven luminous flux compensation method for ring-array photoacoustic imaging system

Photoacoustic imaging technology combines the advantages of pure optical imaging and pure acoustic imaging. Its imaging depth far exceeds optical imaging and can maintain high imaging resolution, but it is still limited by light attenuation, making it difficult to achieve high-quality image reconstruction of deep tissues. This article studies a data-driven light flux compensation algorithm that utilizes the similarity between light energy flow density and light energy deposition in the overall trend. Using light energy deposition as a reference, the spatial distribution of light energy flow density is calculated to compensate and restore deep tissue information in photoacoustic images, in order to obtain deep tissue information during the photoacoustic imaging process. And based on the constructed ring array photoacoustic tomography system, experimental verification was carried out, and the light flux compensation was applied to the photoacoustic images of nude mouse torso, which can effectively restore the deep tissue information of nude mouse torso. Entropy represents the richness of image features, and after compensation, the entropy of the photoacoustic image increased from 1.54 to 1.83. Compared to Monte Carlo based methods, the algorithm proposed in this paper has smaller computational complexity and faster processing speed, which is expected to achieve real-time imaging compensation and effectively promote the further development of photoacoustic imaging technology.