Compressed sensing photoacoustic imaging for high-speed imaging with sparse measurement: a theoretical study

Abstract

As a new non-destructive medical imaging technology, photoacoustic imaging combines the advantages of optical imaging and ultrasonic imaging, which has the characteristics of high contrast and strong penetration ability. It can effectively image biological tissues and functions, and be applied to the early diagnosis and treatment of tumors, cardiovascular and cerebrovascular diseases, which has broad prospects for development in the field of biomedicine. When photoacoustic imaging is used to collect a large number of pathological medical images, it is prone to slow data transmission and poor reconstruction effect. In an effort to speed up data transmission and improve image reconstruction quality, this article is based on photoacoustic imaging technology and compressed sensing reconstruction algorithm, a virtual simulation platform of photoacoustic tomography combined with compressive sensing is built by using K-wave simulation toolbox, and the hard thresholding pursuit algorithm is used to complete the signal reconstruction. In order to verify the performance of the virtual simulation platform, in this paper, the local vascular network is compressed and reconstructed. The reconstructed image retains the main information of the original image, and the edge features are similar. The results show that the virtual simulation platform can reconstruct high quality images by a small amount of data, which provides important significance and theoretical research value for the application of the compressed sensing in photoacoustic imaging.