Original Article


Back-projection algorithm in generalized form for circular-scanning-based photoacoustic tomography with improved tangential resolution

Bo Wang, Tianning Su, Weiran Pang, Ningning Wei, Jiaying Xiao, Kuan Peng

Abstract

Background: The back-projection algorithm is the most common method for the reconstruction of circular-scanning-based photoacoustic tomography (CSPAT) due to its simplicity, computational efficiency, and robustness. It usually can be implemented in two models: one for ideal point detector, and the other for planar transducer with infinite element size. However, because most transducers in CSPAT are planar with a finite size, the off-center targets will be blurred in the tangential direction with these two reconstruction models.
Methods: Here in this paper, we put forward a new model of the back projection algorithm for the reconstruction of CSPAT with finite size planar transducer, in which the acoustic spatial temporal response of the employed finite size transducer is approximated with a virtual detector placed at an optimized distance behind the transducer, and the optimized distance is determined by a phase square difference minimization scheme. Notably, this proposed method can also be suitable for reconstruction with the ideal point detector and infinite planar detector, and thus is a generalized form of the back-projection algorithm.
Results: Compared with the two conventional models of the back-projection method and the modified back-projection method, the proposed method in this work can significantly improve the tangential resolution of off-center targets, thus improving the reconstructed image quality. These findings are validated with both simulations and experiments.
Conclusions: We propose a generalized model of the back projection algorithm to restore the elongated tangential resolution in CSPAT in case of a planar transducer of finite size, which can also be applicable for point and large-size planar transducers. This proposed method may also guide the design of CSPAT scanning configurations for potential applications such as human breast imaging for cancer detection.

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