Original Article
Image reconstruction of the absorption coefficients with l1-norm minimization from photoacoustic measurements
Abstract
Background: The photoacoustic (PA) imaging by considering light propagation into image reconstruction process can provide quantitative information of photon absorbers, such as hemoglobin and exogenous dyes, and to improve their imaging contrasts.
Methods: A 2D image reconstruction of the distribution of the light absorption coefficient from the PA measurements with light source and ultrasound transducer placed at the identical position was tested. The PA pressures were formulated with the PA wave equation and the photon diffusion equation. The relation between the PA pressure and the absorption coefficient was linearized. The image reconstruction was carried out by minimizing the squared error between the measured and calculated PA signals. The l1-norm of the reconstructed image was simultaneously minimized to improve the localization of the reconstructed target in the image. The image reconstruction with the l1-norm minimization was compared to that with the Tikhonov regularization by numerical simulation and phantom experiment. In phantom experiment, an aqueous solution of the intralipid and the indocyanine green was used as the measured object. The PA probe had optical fiber for illumination and piezoelectric film for detection placed at the identical position.
Results: The l1-norm minimization reconstructed more localized target than the Tikhonov regularization.
Conclusions: The l1-norm minimization is useful for the sparse PA image reconstruction.
Methods: A 2D image reconstruction of the distribution of the light absorption coefficient from the PA measurements with light source and ultrasound transducer placed at the identical position was tested. The PA pressures were formulated with the PA wave equation and the photon diffusion equation. The relation between the PA pressure and the absorption coefficient was linearized. The image reconstruction was carried out by minimizing the squared error between the measured and calculated PA signals. The l1-norm of the reconstructed image was simultaneously minimized to improve the localization of the reconstructed target in the image. The image reconstruction with the l1-norm minimization was compared to that with the Tikhonov regularization by numerical simulation and phantom experiment. In phantom experiment, an aqueous solution of the intralipid and the indocyanine green was used as the measured object. The PA probe had optical fiber for illumination and piezoelectric film for detection placed at the identical position.
Results: The l1-norm minimization reconstructed more localized target than the Tikhonov regularization.
Conclusions: The l1-norm minimization is useful for the sparse PA image reconstruction.
