Diffuse optical tomography with spectral constraints and wavelength optimization

We present an algorithm that explicitly utilizes the wavelength dependence of tissue optical properties for diffuse optical tomography. We have previously shown that the method gives superior separation of absorption and scattering. Here the technique is described and tested in detail, and optimum wavelength sets for a broad range of chromophore combinations are discovered and analyzed.     

Estimating optical absorption, scattering, and Grueneisen distributions with multiple-illumination photoacoustic tomography

While photoacoustic methods offer significant promise for high-resolution optical contrast imaging, quantification has thus far proved challenging. In this paper, a noniterative reconstruction technique for producing quantitative photoacoustic images of both absorption and scattering perturbations is introduced for the case when the optical properties of the turbid background are known and multiple optical illumination locations are used. Through theoretical developments and computational examples, it is demonstrated that multiple-illumination photoacoustic tomography (MI-PAT) can alleviate ill-posedness due to absorption-scattering nonuniqueness and produce quantitative high-resolution reconstructions of optical absorption, scattering, and Gruneisen parameter distributions. While numerical challenges still exist, we show that the linearized MI-PAT framework that we propose has orders of magnitude improved condition number compared with CW diffuse optical tomography.     

Image correction scheme applied to functional diffuse optical tomography scattering images

We have extended our investigation on the use of a linear algorithm for enhancing the accuracy of diffuse optical tomography (DOT) images, to include spatial maps of the diffusion coefficient. The results show that the corrected images are markedly improved in terms of estimated size, spatial resolution, two-object resolving power, and quantitative accuracy. These image-enhancing effects are significant at expected levels of diffusion-coefficient contrast in tissue and noise levels typical of experimental DOT data. Overall, the types and magnitudes of image-enhancing effects obtained here are qualitatively similar to those seen in previous studies on mu(a) perturbations. The implications for practical implementations of DOT time-series imaging are discussed.     

Multi-frequency diffuse optical tomography

The performance of diffuse optical tomography (DOT) is investigated when multi-modulation frequencies are used simultaneously in the inverse problem in order to cast the forward model. The forward model used was based on the first-order Rytov approximation of the diffusion equation. Numerical measurements were generated with a finite difference approach for configurations relevant to breast optical mammography. The impact of various frequency-set characteristics was evaluated. Furthermore, the effect of sensitivity matrix preconditioning was investigated. The criteria underlying this study were based on a ‘singular value analysis’ and parameter cross-talk between absorption and scattering reconstructions. It had been shown that preconditioning the matrix was necessary to provide accurate results and an even distribution of frequencies within the larger bound. Furthermore, correlating the different criterions used demonstrated that analysis based on optimization of condition number alone was providing misleading results.     

Time-resolved Fourier optical diffuse tomography.

Time-resolved Fourier optical diffuse tomography is a novel approach for imaging of objects in a highly scattering turbid medium with use of an incident (near) plane wave. The theory of the propagation of spatial Fourier components of the scattered wave field is presented, along with a fast algorithm for three-dimensional reconstruction in a parallel planar geometry. Examples of successful reconstructions of simulated hidden absorptive or scattering objects embedded inside a human-tissue-like semi-infinite turbid medium are provided.     

Visible spectral dependence of the scattering and absorption coefficients of pigmented coatings from inversion of diffuse reflectance spectra

A spectral-projected gradient method and an extension of the Kubelka-Munk theory are applied to obtain the relevant parameters of the theory from measured diffuse reflectance spectra of pigmented samples illuminated with visible diffuse radiation. The initial estimate of the spectral dependence of the parameters, required by a recursive spectral-projected gradient method, was obtained by use of direct measurements and up-to-date theoretical estimates. We then tested the consistency of the Kubelka-Munk theory by repeating the procedure with samples of different thicknesses.     

Volume image reconstruction for diffuse optical tomography

Optical tomography is a potential diagnostic method for visualizing optical properties of tissues in vivo. We present an optical tomography method that has been designed for imaging of the human testes, particularly for spectroscopic tumor differentiation. In this application we need to compute three-dimensional distributions of the optical contrast (absorption coefficient) in the tissue in real time. Thus we have given special care to elaborate an efficient inverse algorithm that takes the limitations of spatial resolution and data space point density into account. Our inverse solution is based on a linearization approach and a dedicated object space discretization. Furthermore, we introduce the concept of fuzzy voxels, which enables a reconstruction-inherent image smoothing.     

Optode positional calibration in diffuse optical tomography

Although diffuse optical tomography is a highly promising technique used to noninvasively image blood volume and oxygenation, the reconstructed data are sensitive to systemic difference between the forward model and the actual experimental conditions. In particular, small changes in optode location or in the optode-tissue coupling coefficient significantly degrade the quality of the reconstruction images. Accurate system calibration therefore is an essential part of any experimental protocol. We present a technique for simultaneously calibrating optode positions and reconstructing images that significantly improves image quality, as we demonstrate with simulations and phantom experiments.     

Pseudo-time particle filtering for diffuse optical tomography

We recast the reconstruction problem of diffuse optical tomography (DOT) in a pseudo-dynamical framework and develop a method to recover the optical parameters using particle filters, i.e., stochastic filters based on Monte Carlo simulations. In particular, we have implemented two such filters, viz., the bootstrap (BS) filter and the Gaussian-sum (GS) filter and employed them to recover optical absorption coefficient distribution from both numerically simulated and experimentally generated photon fluence data. Using either indicator functions or compactly supported continuous kernels to represent the unknown property distribution within the inhomogeneous inclusions, we have drastically reduced the number of parameters to be recovered and thus brought the overall computation time to within reasonable limits. Even though the GS filter outperformed the BS filter in terms of accuracy of reconstruction, both gave fairly accurate recovery of the height, radius, and location of the inclusions. Since the present filtering algorithms do not use derivatives, we could demonstrate accurate contrast recovery even in the middle of the object where the usual deterministic algorithms perform poorly owing to the poor sensitivity of measurement of the parameters. Consistent with the fact that the DOT recovery, being ill posed, admits multiple solutions, both the filters gave solutions that were verified to be admissible by the closeness of the data computed through them to the data used in the filtering step (either numerically simulated or experimentally generated).     

Simultaneous mapping of absorption and scattering coefficients from a three-dimensional model of time-resolved optical tomography

A Newton-Raphson inversion algorithm has been extended for simultaneous absorption and scattering reconstruction of fully three-dimensional (3D) diffuse optical tomographic imaging from time-resolved measurements. The proposed algorithm is derived from the efficient computation of the Jacobian matrix of the forward model and uses either the algebraic reconstruction technique or truncated singular-value decomposition as the linear inversion tool. Its validation was examined with numerically simulated data from 3-D finite-element discretization models of tissuelike phantoms, with several combinations of geometric and optical properties, as well as two commonly used source-detector configurations. Our results show that the fully 3-D image reconstruction of an object can be achieved with reasonable quality when volumetric light propagation in tissues is considered, and temporal information from the measurements can be effectively employed. Also, we investigated the conditions under which 3-D issues could be approximately addressed with two-dimensional reconstruction algorithms and further demonstrated that these conditions are seldom predictable or attainable in practice. Thus the application of 3-D algorithms to realistic situations is necessary.     

Spatially variant regularization improves diffuse optical tomography

Diffuse tomography with near-infrared light has biomedical application for imaging hemoglobin, water, lipids, cytochromes, or exogenous contrast agents and is being investigated for breast cancer diagnosis. A Newton-Raphson inversion algorithm is used for image reconstruction of tissue optical absorption and transport scattering coefficients from frequency-domain measurements of modulated phase shift and light intensity. A variant of Tikhonov regularization is examined in which radial variation is allowed in the value of the regularization parameter. This method minimizes high-frequency noise in the reconstructed image near the source-detector locations and can produce constant image resolution and contrast across the image field.     

Iterative boundary method for diffuse optical tomography

The recent application of tomographic methods to three-dimensional imaging through tissue by use of light often requires modeling of geometrically complex diffuse-nondiffuse boundaries at the tissue-air interface. We have recently investigated analytical methods to model complex boundaries by means of the Kirchhoff approximation. We generalize this approach using an analytical approximation, the N-order diffuse-reflection boundary method, which considers higher orders of interaction between surface elements in an iterative manner. We present the general performance of the method and demonstrate that it can improve the accuracy in modeling complex boundaries compared with the Kirchhoff approximation in the cases of small diffuse volumes or low absorption. Our observations are also contrasted with exact solutions. We furthermore investigate optimal implementation parameters and show that a second-order approximation is appropriate for most in vivo investigations.     

Inverse scattering for optical coherence tomography

Inverse scattering theory for optical coherence tomography (OCT) is developed. The results are used to produce algorithms to resolve three-dimensional object structure, taking into account the finite beam width, diffraction, and defocusing effects. The resolution normally achieved only in the focal plane of the OCT system is shown to be available for all illuminated depths in the object without moving the focal plane. Spatially invariant resolution is verified with numerical simulations and indicates an improvement of the high-resolution cross-sectional imaging capabilities of OCT.     

Determination of Kubelka-Munk scattering and absorption coefficients by diffuse illumination

The Kubelka-Munk theory, although it provides an equation that relates the reflection of a sample under diffuse illumination to certain of its properties, does not take boundary reflectance into account. Boundary reflection is always present because there is always a difference between the refractive indices of the sample and of the surrounding medium. We describe how a half-sphere is used to achieve diffuse illumination, and we present and exemplify equations that correct for boundary reflection with measurements of four composite restorative dental materials. The refractive index of the sample is measured with a matching technique that employs a glycerol-water mixture. Edge loss errors are estimated.     

Noncontact fluorescence diffuse optical tomography of heterogeneous media

Fluorescence-enhanced diffuse optical tomography is expected to be useful to the collection of functional information from small animal models. This technique is currently limited by the extent of tissue heterogeneity and management of the shape of the animals. We propose an approach based on the reconstruction of object heterogeneity, which provides an original solution to the two problems. Three evaluation campaigns are described: the first two were performed on phantoms designed to test the reconstructions in highly heterogeneous media and noncontact geometries; the third was conducted on mice with lung tumors to test fluorescence yield reconstruction feasibility in vivo.     

海水光谱吸收/散射系数测量仪的研制

在克服了由于海水的光谱吸收和散射很小的难点下,研制成功具有高分辨和高精度能力的室外现场测试仪器,其结构紧凑合理,测量装置构思精巧,测试过程完全自动化,克服环境和测试条件的多变性带来的影响,实现了海水吸收系数与散射系数的瞬态测量。现场海水光谱吸收/散射系统测量装置为国内首创,填补了国内空白。     

Optimal linear inverse solution with multiple priors in diffuse optical tomography

A general framework for incorporating single and multiple priors in diffuse optical tomography is described. We explore the use of this framework for simultaneously utilizing spatial and spectral priors in the context of imaging breast cancer. The utilization of magnetic resonance images of water and lipid content as a statistical spatial prior for the diffuse optical image reconstructions is also discussed. Simulations are performed to demonstrate the significant improvement in image quality afforded by combining spatial and spectral priors.     

Spatially resolved absolute diffuse reflectance measurements for noninvasive determination of the optical scattering and absorption coefficients of biological tissue

The absorption and transport scattering coefficients of biological tissues determine the radial dependence of the diffuse reflectance that is due to a point source. A system is described for making remote measurements of spatially resolved absolute diffuse reflectance and hence noninvasive, noncontact estimates of the tissue optical properties. The system incorporated a laser source and a CCD camera. Deflection of the incident beam into the camera allowed characterization of the source for absolute reflectance measurements. It is shown that an often used solution of the diffusion equation cannot be applied for these measurements. Instead, a neural network, trained on the results of Monte Carlo simulations, was used to estimate the absorption and scattering coefficients from the reflectance data. Tests on tissue-simulating phantoms with transport scattering coefficients between 0.5 and 2.0 mm(-1) and absorption coefficients between 0.002 and 0.1 mm(-1) showed the rms errors of this technique to be 2.6% for the transport scattering coefficient and 14% for the absorption coefficients. The optical properties of bovine muscle, adipose, and liver tissue, as well as chicken muscle (breast), were also measured ex vivo at 633 and 751 nm. For muscle tissue it was found that the Monte Carlo simulation did not agree with experimental measurements of reflectance at distances less than 2 mm from the incident beam.     

Implementation of edge-preserving regularization for frequency-domain diffuse optical tomography

In this study, we first propose the use of edge-preserving regularization in optimizing an ill-conditioned problem in the reconstruction procedure for diffuse optical tomography to prevent unwanted edge smoothing, which usually degrades the attributes of images for distinguishing tumors from background tissues when using Tikhonov regularization. In the edge-preserving regularization method presented here, a potential function with edge-preserving properties is introduced as a regularized term in an objective function. With the minimization of this proposed objective function, an iterative method to solve this optimization problem is presented in which half-quadratic regularization is introduced to simplify the minimization task. Both numerical and experimental data are employed to justify the proposed technique. The reconstruction results indicate that edge-preserving regularization provides a superior performance over Tikhonov regularization.