To fully realize the potential of photoacoustic tomography (PAT) in preclinical and clinical applications, rapid measurements and robust reconstructions are needed. Sparse-view measurements have been adopted effectively to accelerate the data acquisition. However, since the reconstruction from the sparse-view sampling data is challenging, both of the effective measurement and the appropriate reconstruction should be taken into account. In this study, we present an iterative sparse-view PAT reconstruction scheme where a virtual parallel-projection concept matching for the proposed measurement condition is introduced to help to achieve the “compressive sensing” procedure of the reconstruction, and meanwhile the spatially adaptive filtering fully considering the a priori information of the mutually similar blocks existing in natural images is introduced to effectively recover the partial unknown coefficients in the transformed domain. Therefore, the sparse-view PAT images can be reconstructed with higher quality compared with the results obtained by the universal back-projection (UBP) algorithm in the same sparse-view cases. The proposed approach has been validated by simulation experiments, which exhibits desirable performances in image fidelity even from a small number of measuring positions.
CW radiance measurements examine the light intensity at a single source-detector location from different detection directions to recover absorption coefficient and reduced scattering coefficient of the turbid medium which is important in treatment planning of minimally invasive laser therapies. In this paper, P9 approximation for radiance is used as the forward model for fitting by considering the balance between computational time and the correctness of the forward model at low albedo and small source detector separation (SDS). By fitting P9 approximation for radiance to the angular radiance Monte Carlo (MC) simulations used as the angular radiance measurements, optical parameters are recovered over a wide range of reduced albedo between 0.69 and 0.99 at small SDS 2mm. The recovery errors of absorption coefficient and reduced scattering coefficient are less than 11.96% and 2.63%, respectively. The effects of the maximum angle used for fitting on optical parameter recovery have been further studied. The results show that the recovery errors of absorption coefficient and reduced scattering coefficient are less than 12% and 3% respectively when the maximum angle is greater than 70 degree.
Coupling between transport theory and its diffusion approximation in subdomain-based hybrid models for enhanced description of near-field photon-migration can be computationally complex, or even physically inaccurate. We report on a physically consistent coupling method that links the transport and diffusion physics of the photons according to transient photon kinetics, where distribution of the fully diffusive photons at a transition time is provided by a computation-saving auxiliary time-domain diffusion solution. This serves as a complementary or complete isotropic source of the temporally integrated transport equation over the early stage and the diffusion equation over the late stage, respectively, from which the early and late photodensities can be acquired independently and summed up to achieve steady-state modeling of the whole transport process. The proposed scheme is validated with numerical simulations for a cubic geometry.
Shape-parameterized diffuse optical tomography (DOT), which is based on a priori that assumes the uniform distribution
of the optical properties in the each region, shows the effectiveness of complex biological tissue optical heterogeneities
reconstruction. The priori tissue optical structure could be acquired with the assistance of anatomical imaging methods
such as X-ray computed tomography (XCT) which suffers from low-contrast for soft tissues including different optical
characteristic regions. For the mouse model, a feasible strategy of a priori tissue optical structure acquisition is proposed
based on a non-rigid image registration algorithm. During registration, a mapping matrix is calculated to elastically align
the XCT image of reference mouse to the XCT image of target mouse. Applying the matrix to the reference atlas which
is a detailed mesh of organs/tissues in reference mouse, registered atlas can be obtained as the anatomical structure of
target mouse. By assigning the literature published optical parameters of each organ to the corresponding anatomical
structure, optical structure of the target organism can be obtained as a priori information for DOT reconstruction
algorithm. By applying the non-rigid image registration algorithm to a target mouse which is transformed from the
reference mouse, the results show that the minimum correlation coefficient can be improved from 0.2781 (before
registration) to 0.9032 (after fine registration), and the maximum average Euclid distances can be decreased from
12.80mm (before registration) to 1.02mm (after fine registration), which has verified the effectiveness of the algorithm.
Radiance is sensitive to the variations of tissue optical parameters, such as absorption coefficient μa, scattering coefficient μs, and anisotropy factor g. Therefore, similar to fluence, radiance can be used for tissue characterization. Compared with fluence, radiance has the advantage of offering the direction information of light intensity. Taking such advantage, the optical parameters can be determined by rotating the detector through 360 deg with only a single optode pair. Instead of the translation mode used in the fluence-based technologies, the Rotation mode has less invasiveness in the clinical diagnosis. This paper explores a new method to obtain the optical properties by measuring the distribution of light intensity in liquid phantom with only a single optode pair and the detector rotation through 360 deg. The angular radiance and distance-dependent radiance are verified by comparing experimental measurement data with Monte Carlo (MC) simulation for the short source-detector separations and diffusion approximation for the large source-detector separations. Detecting angular radiance with only a single optode pair under a certain source-detection separation will present a way for prostate diagnose and light dose calculation during the photon dynamic therapy (PDT).
As a new non-invasive medical imaging technology, diffuse optical tomography (DOT) has received considerable attention that can provide vast quantities of functional information of tissues. The reconstruction problem of DOT is highly ill-posed, meaning that a small error in the measurement data can bring about drastic errors of the reconstruction optical properties. In this paper, the shape-based image reconstruction algorithm of DOT is proposed for reducing the ill-poseness under the assumption that the optical properties of target region distribute uniformly. Since some human organs and tumors can be simplified as an ellipsoid, in this paper, the shape of the inhomogeneity is described as an ellipsoid. In the forward problem, the boundary element method (BEM) is implemented to solve the continuous wave diffusion equation (DE). By the use of the ellipsoid parametric method, the description of the shape, location and optical properties of the inhomogeneity, and the value of the background could be realized with only a small number of parameters. In the inverse calculation, a Levenberg-Marquardt algorithm with line searching is implemented to solve the underlying nonlinear least-squares problem. Simulation results show that the algorithm developed in this paper is effective in reducing the ill-poseness and robust to the noise.
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