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We outline a computationally efficient image correction algorithm, which we have applied to diffuse optical tomography (DOT) image time series derived from a magnetic resonance imaging (MRI)-based brain model. Results show that the algorithm increases spatial resolution, decreases spatial bias, and only modestly reduces temporal accuracy for noise levels typically seen in experiment, and produces results comparable to image reconstructions that incorporate information from MRI priors. We demonstrate that this algorithm has robust performance in the presence of noise, background heterogeneity, irregular external and internal boundaries, and error in the initial guess. However, the algorithm introduces artifacts when the absorption and scattering coefficients of the reference medium are overestimated--a situation that is easily avoided in practice. The considered algorithm offers a practical approach to improving the quality of images from time-series DOT, even without the use of MRI priors. OCIS codes: 100.1830, 100.2980, 100.6890, 100.6950, 170.3010, 170.3880.

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].sub.a] perturbations. The implications for practical implementations of DOT time-series imaging are discussed. OCIS codes: 100.1830, 100.2980, 100.6950, 170.3010, 170.3880.

Dynamic near-infrared optical tomographic measurement instrumentation capable of simultaneous bilateral breast imaging, having a capability of four source wavelengths and 32 source-detector fibers for each breast, is described. The system records dynamic optical data simultaneously from both breasts, while verifying proper optical fiber contact with the tissue through implementation of automatic schemes for evaluating data integrity. Factors influencing system complexity and performance are discussed, and experimental measurements are provided to demonstrate the repeatability of the instrumentation. Considerations in experimental design are presented, as well as techniques for avoiding undesirable measurement artifacts, given the high sensitivity and dynamic range (1:[10.sup.9]) of the system. We present exemplary clinical results comparing the measured physiologic response of a healthy individual and of a subject with breast cancer to a Valsalva maneuver.

Systematic characterization studies are presented, relating to a previously reported spatial deconvolution operation that seeks to compensate for the information-blurring property of first-order perturbation algorithms for diffuse optical tomography (DOT) image reconstruction. In simulation results that are presented, this deconvolution operation has been applied to two-dimensional DOT images reconstructed by solving a first-order perturbation equation. Under study was the effect on algorithm performance of control parameters in the measurement (number and spatial distribution of sources and detectors, presence of noise, and presence of systematic error), target (medium shape; and number, location, size, and contrast of inclusions), and computational (number of finite-element-method mesh nodes, length of filter-generating linear system, among others) parameter spaces associated with computation and the use of the deconvolution operators. Substantial improvements in reconstructed image quality, in terms of recovered inclusion location, size, and contrast, are found in all cases. A finding of practical importance is that the method is robust to appreciable differences between the optical coefficients of the media used for filter generation and those of the target media to which the filters are subsequently applied.

A straightforvard spatial deconvolution operation is presented that seeks to invert the information-blurring property of first-order perturbation algorithms for diffuse optical tomography (DOT) image reconstruction. The method that was developed to generate these deconvolving operators, or filters, was conceptually based on the frequency-encoding process used in magnetic resonance imaging. The computation of an image-correcting filter involves the solution of a large system of linear equations, in which known true distributions and the corresponding recovered distributions are compared. Conversely, application of a filter involves only a simple matrix multiplication. Simulation results show that application of this deconvolution operation to three-dimensional DOT images reconstructed by the solution of a first-order perturbation equation (Born approximation) can yield marked enhancement of image quality. In the examples considered, use of image-correcting filters produces obvious improvements in image quality, in terms of both location and [[mu].sub.a] of the inclusions. The displacements between the true and recovered locations of an inclusion's centroid location are as small as 1 mm, in an 8-cm-diameter medium with 1.5 cm-diameter inclusions, and the peak value of the recovered [[mu].sub.a], for the inclusions deviates from the true value by as little as 5%. OCIS codes: 170.3880, 170.3010, 100.1830, 100.6950, 100.6890.

The utility of optical tomography as a practical imaging modality has, thus far, been limited by its intrinsically low spatial resolution and quantitative accuracy. Recently, we have argued that a broad range of physiological phenomena might be accurately studied by adopting this technology to investigate dynamic states (Schmitz et al., 2000; Barbour et al., 2000; Graber et al., 2000; Barbour et al., 2001; and Barbour et al., 1999). One such phenomenon holding considerable significance is the dynamics of the vasculature, which has been well characterized as being both spatially and temporally heterogeneous. In this paper, we have modeled such heterogeneity in the limiting case of spatiotemporal coincident behavior involving optical contrast features, in an effort to define the expected limits with which dynamic states can be characterized using two newly described reconstruction methods that evaluate normalized detector data: the normalized difference method (NDM) and the normalized constraint method (NCM). Influencing the design of these studies is the expectation that spatially coincident temporal variations in both the absorption and scattering properties of tissue can occur in vivo. We have also chosen to model dc illumination techniques, in recognition of their favorable performance and cost for practical systems. This choice was made with full knowledge of theoretical findings arguing that separation of the optical absorption and scattering coefficients under these conditions is not possible. Results obtained show that the NDM algorithm provides for good spatial resolution and excellent characterization of the temporal behavior of optical properties but is subject to interparameter crosstalk. The NCM algorithm, while also providing excellent characterization of temporal behavior, provides for improved spatial resolution, as well as for improved separation of absorption and scattering coefficients. A discussion is provided to reconcile these findings with theoretical expectations. Index Terms--Crosstalk and nonuniqueness, dynamic optical tomography, inverse problem, physiological dynamics, physiological oscillations.

Two one-speed radiation transport equations coupled by a dynamic equation for the distribution of fluorophore electronic states are used to model the migration of excitation photons and emitted fluorescence photons. The conditions for producing appreciable levels of fluorophore in the excited state are studied, with the conclusion that minimal saturation occurs under the conditions applicable to tissue imaging. This simplifies the derivation of the frequency response and of the imaging operator for a time-harmonic excitation source. Several factors known to influence the fluorescence response - the concentration, mean lifetime and quantum yield of the fluorophore, and the modulation frequency of the excitatory source - are examined. Optimal sensitivity conditions are obtained by analyzing the fluorescence source strength as a function of the mean lifetime and modulation frequency. The dependence of demodulation of the fluorescent signal on the above factors is also examined. In complementary studies, transport-theory-based operators for imaging fluorophore distributions in a highly scattering medium are derived. Experimental data were collected by irradiating a cylindrical phantom containing one or two fluorophore-filled balloons with continuous wave laser light. The reconstruction results show that qualitatively and quantitatively good images can be obtained, with embedded objects accurately located and the fluorophore concentration correctly determined. Index Terms - Image reconstruction, luminescent materials/ devices, optical imaging, random media, tomography.

In this paper, we present a wavelet-based multigrid approach to solve the perturbation equation encountered in optical tomography. With this scheme, the unknown image, the data, as well as the weight matrix are all represented by wavelet expansions, thus yielding a multiresolution representation of the original perturbation equation in the wavelet domain. This transformed equation is then solved using a multigrid scheme, by which an increasing portion of wavelet coefficients of the unknown image are solved in successive approximations. One can also quickly identify regions of interest (ROI's) from a coarse level reconstruction and restrict the reconstruction in the following fine resolutions to those regions. At each resolution level a regularized least squares solution is obtained using the conjugate gradient descent method. This approach has been applied to continuous wave data calculated based on the diffusion approximation of several two-dimensional (2-D) test media. Compared to a previously reported one grid algorithm, the multigrid method requires substantially shorter computation time under the same reconstruction quality criterion. Index Terms - Image reconstruction, multigrid method, optical tomography, wavelet transform.

We present a model suitable for computing images of absorption cross sections of thick tissue structures illuminated at near infrared (NIR) wavelengths from tomographic projection data. Image reconstruction is accomplished by solving a system of linear equations derived from transport theory. Reconstruction results using different algebraic solvers are shown for anatomical maps of the breast, derived from magnetic resonance imaging data, containing two simulated pathologies, in which case qualitatively good reconstructions were obtained. Evaluation of magnetic resonance (MR) data to optimize NIR optical tomographic imaging methods and to assess the feasibility of a combined MR-optical measurement scheme is discussed. Index Terms - Dense scattering medium, inverse problem, optical tomography.

We present a useful strategy for imaging perturbations of the macroscopic absorption cress section of dense-scattering media using steady-state light sources. A perturbation model based on transport theory is derived, and the inverse problem is simplified to a system of linear equations, W[Delta][Mu] = [Delta]R, where W is the weight matrix, [Delta][Mu] is a vector of the unknown perturbations, and [Delta]R is the vector of detector readings. Monte Carlo simulations compute the photon flux across the surfaces of phantoms containing simple or complex inhomogeneities. Calculation of the weight matrix is also based on the results of Monte Carlo simulations. Three reconstruction algorithms - conjugate gradient descent, projection onto convex sets, and the simultaneous algebraic reconstruction technique, with or without imposed positivity constraints - are used for image reconstruction. A rescaling technique that improves the conditioning of the weight matrix is also developed. Results show that the analysis of time-independent data by a perturbation model is capable of resolving the internal structure of a dense-scattering medium. Imposition of positivity constraints improves image quality at the cost of a reduced convergence rate. Use of the rescaling technique increases the initial rate of convergence, resulting in accurate images in a smaller number of iterations. Key words: Dense-scattering medium, inverse problem, perturbation, ill posed.

Instrumentation is described that is suitable for acquiring multisource, multidetector, time-series optical data at high sampling rates (up to 150 Hz) from tissues having arbitrary geometries. The design rationale, calibration protocol, and measured performance features are given for both a currently used, CCD-camera-based instrument and a new silicon-photodiode-based system under construction. Also shown are representative images that we reconstructed from data acquired in laboratory studies using the described CCD-based instrument. [C] 2000 Optical Society of America OCIS codes: 170.3880, 170.3890, 170.1610, 170.5380, 170.3830.