KRLODPLSMR-GCV3DC—improving contrast-based photoacoustic imaging based on model reconstruction

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.