Contrast-based photoacoustic imaging is an emerging imaging technology that gold nanoparticles (a kind of photoacoustic contrast agent with a size of 100 nm) are injected into blood vessels for photoacoustic imaging. Image reconstruction is a critical step in photoacoustic imaging, due to the fact that limitations and incompleteness of photoacoustic imaging data of image reconstruction are equivalent to the linear inverse problems. The photoacoustic data is transferred to IOT based on the platform of MATLAB and is quickly processed through the regularization method of Krylov space (the widely used method is LSQR). In order to solve the problem of Krylov space uncertainty, Krylov space dimension selection, and the minimum mismatch of the LSQR objective function (the limitation of LSQR algorithm) of LSQR algorithm, a KRLODPLSMR-GCV3DC algorithm is proposed to solve the above problems in this paper.In this study, the raw photoacoustic data was obtained by injecting gold nanoparticles into capillaries and subcutaneous veins of the palm, and the KRLODPLSMR-GCV3DC algorithm was verified to solve the limitations of LSQR algorithm through four groups of experiments.

基于对比度的光声成像是一种新兴的成像技术，将金纳米颗粒（一种尺寸为100 nm的光声造影剂）注入血管中以进行光声成像。由于图像重建的光声成像数据的局限性和不完整性等同于线性逆问题，因此图像重建是光声成像的关键步骤。基于MATLAB平台，将光声数据传输到IOT，并通过Krylov空间的正则化方法（广泛使用的方法是LSQR）对其进行快速处理。为了解决Krylov空间不确定性，Krylov空间维数选择以及LSQR算法的LSQR目标函数的最小失配问题（LSQR算法的局限性），