LAUSR

Image formation in photoacoustic tomography (PAT) is generally based on the assumption that biological tissues are acoustically homogeneous. However, this does not hold, especially when strongly heterogeneous tissues, such as bones and air cavities, are present. Tissue heterogeneity can cause acoustic reflection, refraction, and scattering at interfaces, which may create distortions and artifacts in final images. To mitigate this problem, we propose an adaptive photoacoustic (PA) image reconstruction method based on prior structural information of an acoustically heterogeneous region extracted from ultrasound images. The method works in three steps: acoustic heterogeneity identification via ultrasound imaging; acoustically heterogeneous region segmentation; and adaptive time-domain raw data truncation and image reconstruction. The data truncation is based on a variable cutoff time, which can be adaptively determined according to the relative position of a transducer and an acoustically heterogeneous region. Numerical and in vivo experimental imaging results of human fingers demonstrate that the proposed ultrasound-guided adaptive image reconstruction method can effectively suppress acoustic heterogeneity-induced artifacts and substantially improve image quality. This work provides a practical way to mitigate the influence of acoustic heterogeneity in PAT.