Speckles have been considered ubiquitous in all scattering-based coherent imaging technologies. However, as an optical-absorption-based coherent imaging technology, photoacoustic (PA) tomography (PAT) suppresses speckles by building up prominent boundary signals. We theoretically study the dependence of PAT speckles on the boundary roughness, which is quantified by the root-mean-squared value and the correlation length of the boundary height. Both the speckle visibility and the correlation coefficient between the reconstructed and actual boundaries are quantified. If the root-mean-squared height fluctuation is much greater than, and the height correlation length is much smaller than the imaging resolution, the reconstructed boundaries become fully developed speckles. In other words, speckle formation requires large uncorrelated height fluctuations within the resolution cell. The first- and second-order statistics of PAT speckles are also studied experimentally. While the amplitude of the speckles follows a Gaussian distribution, the autocorrelation of the speckle patterns tracks that of the system point spread function.
The penetration depth of ballistic optical imaging technologies is limited by light scattering. To study the effect of
scattering on optical-resolution photoacoustic microscopy (OR-PAM), we divided the signals in OR-PAM into two
classes: one is from the target volume defined by the optical resolution cell (Class I); the other is from the rest of the
acoustic resolution cell (Class II). We developed a way to simulate the point spread function (PSF) of our OR-PAM
system considering both optical illumination and acoustic detection, then used the PSF to calculate the contributions of
each class of signal to the total signal at different focal depths. Our simulation results showed that: 1) The Class II
signal decays much more slowly than the Class I signal; 2) The full width at half maximum (FWHM) of the PSF for the
focal depth of 0.9 transport mean free path (TMFP) is not broadened much (~10%) compared with that for a clear
medium; 3) Image contrast is degraded with increasing depth when there is a uniform absorption background.
Photoacoustic tomography (PAT) suppresses speckles by prominent boundary buildups. We theoretically study the
dependence of PAT speckles on the boundary roughness, which is quantified by the root-mean-squared (RMS) value and
the correlation length of the height. The speckle visibility and the correlation coefficient between the reconstructed and
actual boundaries are quantified as a function of the boundary roughness. The statistics of PAT speckles is studied
For the first time, we have implemented photoacoustic tomography (PAT) to image the water content of an edema in vivo. We produced and imaged a cold-induced cerebral edema transcranially, then obtained blood vessel and water accumulation images at 610 and 975 nm, respectively. We tracked the changes at 12, 24, and 36 h after the cold injury. The blood volume decreased after the cold injury, and the maximum area of edema was observed 24 h after the cold injury. We validated PAT of the water content of the edema through magnetic Resonance Imaging and the water spectrum from the spectrophotometric measurement.
As an emerging imaging technique that combines high optical contrast and ultrasonic detection, photoacoustic
tomography (PAT) has been widely used to image optically absorptive objects in both human and animal tissues. PAT
overcomes the depth limitation of other high-resolution optical imaging methods, and it is also free from speckle
artifacts. To our knowledge, water has never been imaged by PAT in biological tissue. Here, for the first time, we
experimentally imaged water in both tissue phantoms and biological tissues using a near infrared (NIR) light source. The
differences among photoacoustic images of water with different concentrations indicate that laser-based PAT can
usefully detect and image water content in tissue.
Photoacoustic tomography (PAT) has been widely used to image optically absorptive objects in both human and animal tissues. For the first time, we present imaging of water with laser-based PAT. We photoacoustically measure the absorption spectra of water-ethanol mixtures at various water concentrations, and then image water-ethanol and pure-water inclusions in gel and a water inclusion in fat tissue. The significant difference in photoacoustic signals between water and fat tissue indicates that the laser-based PAT has the potential to detect water content in tissue.
Fluorescence molecular tomography (FMT) can obtain a sufficient data set and optimal three-dimensional images when
projections are captured over 360° by CCD camera. In the Tikhonov regularization-based reconstruction procedure of
FMT, the optimal regularization parameter obtained by some parameter-choice methods might miss the accurate result
due to the model-mismatch and discretization error. Herein a two-step algorithm was proposed. In the first step, a
suboptimal parameter was estimated based on the expected value of the Fourier coefficient of perturbation. Then in the
second step, the L-curve criterion was adopted to get the optimal parameter in the permissible region obtained in the first
step. With the optimal parameter and permissible region, more accurate reconstruction result was acquired.
Experimental results suggested that such technique outperform the traditional L-curve criterion when applying into the