In photoacoustic tomography (PAT) systems, the tangential resolution decreases due to the finite size of the transducer as the off-center distance increases. To address this problem, we propose a multi-angle detection approach in which the transducer used for data acquisition rotates around its center (with specific angles) as well as around the scanning center. The angles are calculated based on the central frequency and diameter of the transducer and the radius of the region-of-interest (ROI). Simulations with point-like absorbers (for point-spread-function evaluation) and a vasculature phantom (for quality assessment), and experiments with ten 0.5 mm-diameter pencil leads and a leaf skeleton phantom are used for evaluation of the proposed approach. The results show that a location-independent tangential resolution is achieved with 150 spatial sampling and central rotations with angles of ±8°/±16°. With further developments, the proposed detection strategy can replace the conventional detection (rotating a transducer around ROI) in PAT.

In circular photoacoustic computed tomography, for data acquisition, a single-element transducer rotates around the region of interest (ROI). Due to the limited acceptance angle of the finite size transducer, the reconstructed image becomes blurred, and tangential resolution/contrast degrades in off-center locations in the ROI. In this paper, we propose a compensation method in which in addition to the circular scanning, the transducer rotates around its center (with specific angles) at each detection point. The superposition of these central rotations and non-rotated transducer mimics a virtual detector with a wide acceptance angle. The angles are calculated based on the central frequency and diameter of the transducer and the radius of the region-of-interest. Three types of numerical phantom (point-like, vasculature and Derenzo) were used to evaluate the performance of our method. Features of Olympus NDT, V326-SU transducer were used to assemble the numerical data. The results show that the proposed method provides better structural information by lowering the image blurring, improves the tangential resolution by 90% and increases peak signal-to-noise ratio by 14%.