Virtual platform of photoacoustic tomography based on K-Wave

Photoacoustic imaging is a biological non-destructive and non-invasive detection method based on the photoacoustic effect. It not only has the advantages of high optical imaging accuracy, high speed, and high contrast, but also has the advantages of good tissue penetration of ultrasound imaging. Early diagnosis of diseases, molecular optics, brain science and other fields have a wide range of applications. However, because the photoacoustic imaging technology is a multi-modal hybrid imaging technology, the research of this technology often requires expensive experimental equipment, and the experimental operation is complicated. Based on the K-Wave toolbox in Matlab, this paper builds a simulation platform for photoacoustic signals. Using this platform, successfully simulate the process of the ultrasonic signal emitted by the sample after absorbing the pulsed laser, and different numbers of sensors were used to collect the signal, and multiple sets of reconstructed images were obtained through back projection. By analyzing the relationship between the number of sensors and the reconstructed image and its signal-to-noise ratio and signal distribution, it is obtained that when the number of sensors is 50, the reconstructed image is clearer, the reconstructed signal distribution is closer to the original signal, and the signal-to-noise ratio is high. When the number of sensors gradually increased to 100, the reconstructed image, signal distribution, and signal-to-noise ratio did not change significantly, but the number of sensors doubled. Due to the high price of sensors, 50 to 100 sensors can be selected (or 50-100 angles can be scanned), which can reduce imaging time and cost while ensuring high imaging quality. Simulation platform of photoacoustic tomography base on K-Wave has the advantages of fast and convenient operation, and can complete the reconstruction of photoacoustic signals with high quality. From the relationship between the number of sensors and the signal distribution and signal-to-noise ratio of the reconstructed image, the influence of the number of sensors on the simulation effect can be obtained, which provides theoretical guidance for the application of photoacoustic imaging in biomedicine.