A Spatial-Domain Factor for Sparse-Sampling Circular-View Photoacoustic Tomography

Abstract

Circular full-view configuration of photoacoustic imaging systems (C-PAI) has many applications in biomedicine (e.g., breast and brain imaging). To obtain a high-quality reconstructed image, dense spatial sampling (a large number of acoustic detectors) is needed, which makes the system expensive and challenging. Unfortunately, by reducing the number of spatial samples, streak artifacts appear, which degrade the quality of the reconstructed image. In this article, we propose a spatial-domain factor to suppress the streak artifacts and enhance the reconstructed image quality in a sparse sampling C-PAI system. Numerical and experimental studies are conducted to evaluate the proposed method. The results show that by reducing the number of spatial samples by one-fifth of the minimum required value to meet the Nyquist criteria, the proposed method provides a higher quality reconstructed image in terms of artifacts suppression and resolution improvement compared to the conventional method with dense spatial sampling. The proposed method improves the structural similarity index measure (SSIM), generalized contrast-to-noise ratio (gCNR), CNR, and tangential resolution values up to 100%, 9%, 38.6 dB, and ∼45%, respectively. Based on the advantages of the proposed method, a low-cost version of a C-PAI system for clinical applications can be developed.