An Efficient Compensation Method for Limited-View Photoacoustic Imaging Reconstruction Based on Gerchberg–Papoulis Extrapolation

The reconstruction for limited-view scanning, though often the case in practice, has remained a difficult issue for photoacoustic imaging (PAI). The incompleteness of sampling data will cause serious artifacts and fuzziness in those missing views and it will heavily affect the quality of the image. To solve the problem of limited-view PAI, a compensation method based on the Gerchberg–Papoulis (GP) extrapolation is applied into PAI. Based on the known data, missing detectors elements are estimated and the image in the missing views is then compensated using the Fast Fourier Transform (FFT). To accelerate the convergence speed of the algorithm, the total variation (TV)-based iterative algorithm is incorporated into the GP extrapolation-based FFT-utilized compensation method (TV-GPEF). The effective variable splitting and Barzilai–Borwein based method is adopted to solve the optimization problem. Simulations and in vitro experiments for both limited-angle circular scanning and straight-line scanning are conducted to validate the proposed algorithm. Results show that the proposed algorithm can greatly suppress the artifacts caused by the missing views and enhance the edges and the details of the image. It can be indicated that the proposed TV-GPEF algorithm is efficient for limited-view PAI.