Photoacoustic Imaging with a Finite-Size Circular Integrating Detector

Photoacoustic imaging (PAI) has rapidly developed in biomedical imaging. The point spread function (PSF) is critical for addressing image blurring in PAI. However, in circular integrating detection systems, the PSF exhibits spatial variations. This makes PSF extraction challenging. The existing studies typically assume that the PSF is known or obtained through experiments. This study proposes a method for extracting the PSF based on the polar coordinate system. By transforming the image from the Cartesian coordinate system to the polar coordinate system, the “spin blur” problem is decomposed into multiple independent subproblems. With the separation of the radial and angular directions, the blurring kernel remains invariant at each radius, thereby simplifying the estimation of the PSF. To estimate the blurring kernel, we use polynomial algebraic common factor extraction techniques. The numerical simulation results validate the effectiveness of the method, and the impact of sample size on computational efficiency and accuracy is discussed.