Enhancing image quality in circular-view photoacoustic tomography using randomized detection points

Abstract Circular-view (circular scan) photoacoustic computed tomography (PACT) with low-density detection points (DPs) is an efficient, high-speed, and inexpensive modality with numerous (pre-) clinical applications. However, as the number of DPs decreases (decrease in A-lines), some unwanted streak artifacts appear in the reconstructed PACT image. Here, we present an approach to address the mentioned challenge and enhance image contrast. In this method, several low-resolution-images (LRIs) are reconstructed by employing a few DPs’ data with randomized locations. These LRIs are used in computing an artifact score matrix (ASM) to identify the location of artifacts. Three numerical (two vasculatures and human brain), two experimental (triangle and complex leaf), and an in vivo (a rat brain) studies were conducted to evaluate the efficacy of the proposed method (applying the computed ASM to the final reconstructed PA image). Our findings show that the proposed method outperforms conventional methods and offers better image quality. The signal-to-noise ratio and structural similarity index values of the proposed method are quantitatively 20 dB and 25% better than the conventional method, respectively. Furthermore, compared to the conventional method, the proposed method has an artifact standard deviation that is 50 times lower.