光声层析(Photoacoustic tomography,PAT)成像结合了超声成像的高分辨率和光学成像的高对比度的优势, 是一种新型的生物医学成像模式。PAT成像算法包含两个逆问题, 即根据组织产生的光声信号构建初始声压分布图(即图像重建)以及在此基础上估算成像区域的光学特性参数。后者是一个非线性的不适定问题, 通常称为定量光声层析(Quantitative photo-acoustic tomography, qPAT)成像。本文在介绍光声成像原理的基础上, 对主要的qPAT算法进行综述, 讨论各自的优势和不足, 并对未来可能的发展方向进行展望。

Photoacoustic tomography (PAT), an emerging medical imaging modality, combines the high resolution of ultrasonic imaging and high contrast of optical imaging. Current research on PAT includes two inverse problems, i.e., constructing the distribution of initial acoustic pressures according to the photo-acoustic signals generated by the tissues and estimating the optical absorption and scattering coefficients of the tissues within the imaging region based on the results of the first inversion. The latter, known as quantitative photoacoustic tomography (qPAT), is in general a nonlinear ill-posed problem. This paper summarizes current algorithms for solving the qPAT inversion. Related advantages and limits as well as perspective studies are discussed.