This PDF file contains the front matter associated with SPIE Proceedings Volume 8088, including the Title Page, Copyright information, Table of Contents, and the Conference Committee listing.

A multimodality approach based on fNIRS-EEG, fMRI-EEG and TMS was used on adult volunteers during motor task aiming at optimizing a functional imaging procedure to be eventually used on patients with movement disorders.

Functional near-infrared spectroscopy (fNIRS) is a commonly used technique to measure the cerebral vascular response related to brain activation. It is known that systemic physiological processes, either independent or correlated with the stimulation task, can influence the optical signal making its interpretation challenging. The aim of the present work is to investigate the impact of task-evoked changes in the systemic physiology on fNIRS measurements for a cognitive paradigm. For this purpose we carried out simultaneous measurements of time-domain fNIRS on the forehead and systemic physiological signals, i.e. mean blood pressure, heart rate, respiration, galvanic skin response, scalp blood flow (flux) and red blood cell (RBC) concentration changes. We performed measurements on 15 healthy volunteers during a semantic continuous performance task (CPT). The optical data was analyzed in terms of depth-selective moments of distributions of times of flight of photons through the tissue. In addition, cerebral activation was localized by a subsequent fMRI experiment on the same subject population using the same task. We observed strong non-cerebral task-evoked changes in concentration changes of oxygenated hemoglobin in the forehead. We investigated the temporal behavior and mutual correlations between hemoglobin changes and the systemic processes. Mean blood pressure (BP), galvanic skin response (GSR) and heart rate exhibited significant changes during the activation period, whereby BP and GSR showed the highest correlation with optical measurements.

Spontaneous cerebral hemodynamic oscillations below 100 mHz reflect the level of cerebral activity, modulate hemodynamic responses to tasks and stimuli, and may aid in detecting various pathologies of the brain. Near-infrared spectroscopy (NIRS) is ideally suited for both measuring spontaneous hemodynamic oscillations and monitoring sleep, but little research has been performed to combine these two applications. We analyzed 30 all-night NIRS-electroencephalography (EEG) sleep recordings to investigate spontaneous hemodynamic activity relative to sleep stages determined by polysomnography. Signal power of hemodynamic oscillations in the low-frequency (LF, 40-150 mHz) and very-low-frequency (VLF, 3-40 mHz) bands decreased in slow-wave sleep (SWS) compared to light sleep (LS) and rapid-eye-movement (REM) sleep. No statistically significant (p < 0.05) differences in oscillation power between LS and REM were observed. However, the period of VLF oscillations around 8 mHz increased in REM sleep in line with earlier studies with other modalities. These results increase our knowledge of the physiology of sleep, complement EEG data, and demonstrate the applicability of NIRS to studying spontaneous hemodynamic fluctuations during sleep.

Robot-assisted motor rehabilitation proved to be an effective supplement to conventional hand-to-hand therapy in stroke patients. In order to analyze and understand motor learning and performance during rehabilitation it is desirable to develop a monitor to provide objective measures of the corresponding brain activity at the rehabilitation progress. We used a portable time-domain near-infrared reflectometer to monitor the hemodynamic brain response to distal upper extremity activities. Four healthy volunteers performed two different robot-assisted wrist/forearm movements, flexion-extension and pronation-supination in comparison with an unassisted squeeze ball exercise. A special headgear with four optical measurement positions to include parts of the pre- and postcentral gyrus provided a good overlap with the expected activation areas. Data analysis based on variance of time-of-flight distributions of photons through tissue was chosen to provide a suitable representation of intracerebral signals. In all subjects several of the four detection channels showed a response. In some cases indications were found of differences in localization of the activated areas for the various tasks.

We demonstrate the simultaneous mapping of haemoglobin oxygenation and blood flow changes of human skin and the exposed cortex in rats by broad-band reflectometry and laser speckle contrast analysis (LASCA). A hard- and software set-up is realized with a high temporal resolution achieved by techniques of multi- and manycore computing. Spatial and temporal resolved changes of haemoglobin oxygenation and blood flow in rats are observed in response to middle cerebral artery occlusion and cortical spreading depression.

Anatomical brain atlases have been introduced in the analysis NIRS data of brain activation and good spatial activation localization has been proved. We applied this method to visualize NIRS data from different protocols.

We report on the development of a scanning non-contact brain imager, based on a novel technique in time-resolved nearinfrared spectroscopy, i.e. the null source-detector distance approach. Our concept is designed to image an area of about 10 cm² with small adjustable scanning steps, i.e. a high density of mapping points can be realized. The feasibility of the proposed method was tested with a single-point confocal optical setup without beam scanning so far. A set of test measurements was performed on a liquid phantom with a small black polyvinyl chloride (PVC) cylinder as a target, which was translated in X direction to emulate the optical scanning and estimate lateral spatial resolution, and in Z direction to estimate the depth sensitivity of the instrument. The problem of dominance of early photons at null sourcedetector separation was solved by applying a fast time-gated detector to detect late only photons. Two fast-gated detectors, a newly developed state-of-art time-gated single-photon avalanche photodiode (tgSPAD) and commercially available fast-gated intensified CCD (iCCD) camera, were compared against each other. It was shown that, due to its better dynamic range, the tgSPAD is capable to detect later photons than the iCCD camera, and hence, a scanning system equipped with the time-gated SPAD has better depth sensitivity. Thus the time-gated SPAD is the detector of choice for further development of the non-contact confocal brain scanner.

Contrary to the intense debate about brain oxygen dynamics and its uncoupling in mammals, very little is known in birds. In zebra finches, picosecond optical tomography (POT) with a white laser and a streak camera can measure in vivo oxy-hemoglobin (HbO₂) and deoxy-hemoglobin (Hb) concentration changes following physiological stimulation (familiar calls and songs). POT demonstrated sufficient sub-micromolar sensitivity to resolve the fast changes in hippocampus and auditory forebrain areas with 250 μm resolution. The time-course is composed of (i) an early 2s-long event with a significant decrease in Hb and HbO₂, respectively -0.7 μMoles/L and -0.9 μMoles/L (ii) a subsequent increase in blood oxygen availability with a plateau of HbO₂ (+0.3μMoles/L) and (iii) pronounced vasodilatation events immediately following the end of the stimulus. One of the findings of our work is the direct link between the blood oxygen level-dependent (BOLD) signals previously published in birds and our results. Furthermore, the early vasoconstriction event and post-stimulus ringing seem to be more pronounced in birds than in mammals. These results in bird, a tachymetabolic vertebrate with a long lifespan, can potentially yield new insights for example in brain aging.

Cerebral blood flow (CBF) change of mice during whisker stimulation is measured by laser speckle flowgraphy (LSFG) and laser Doppler flowmetry (LDF). Laser speckle flowgraphy (LSFG) has been used to obtain the two-dimensional distribution of the blood flow in tissue as well as scanning laser Doppler flowmetry (LDF). There are several parameters of LSFG to obtain the blood flow maps and the distribution change of blood flow. In this study, we calculate four parameters from the speckle pattern to measure CBF in awake mice. The temporal resolution of LSFG is likely to be less than that of LDF. The temporal changes in CBF obtained from the four parameters calculated from the speckle pattern detected by a common CCD camera are compared with those measured by LDF. The time courses of CBF change measured by LSFG highly correlate with those by LDF. The results indicate that the temporal response of LSFG is sufficient to measure CBF change evoked by brain activations.

Light propagation in an N-layered model of the human head is investigated using Monte Carlo simulations and solutions of the diffusion theory. For the inverse problem - the determination of the optical properties of brain or scalp and skull from simulated reflectance curves - a neural network is applied.

Near infrared spectroscopy (NIRS) and diffuse optical tomography (DOT) of the brain reveal no information about the measurement's underlying anatomical structures. An independent anatomical mapping of DOT results onto the subject's brain or a generic brain model is desirable, especially when regions prone to large inter-subject variability are studied. We show two methods to match DOT data from high density fiber grids to anatomical structures. The forward model that is used to predict the light propagation is based on one generic anatomical MR scan. In both approaches we use this model MR-scan to translocate the position of the optical fiber grid from our experimental setup to the FEM model space. The first method, using fiduciary marks, achieves the spatial normalization of the subject's MR-scan (with marked corners of the fiber grid) and the model's MR scan, leading to a translocation of the fiber pad position to the FEM-Model space. The second, anatomic landmark based, approach does not require the individual's MR scan. For this, 19 reference points and the position of the fiber pad corners are determined using photogrammetry software. These coordinates are translocated to the FEM model space by solving the least square problem of the subject's and the model's reference points. We illustrate and compare both methods and show results from a vibrotactile stimulation experiment in humans.

The brain activation image obtained by diffuse optical tomography (DOT) is obtained by solving inverse problem using the spatial sensitivity profile (SSP). The SSP can be obtained from the analysis of the light propagation using threedimensional head models. The head model is based upon segmented magnetic resonance (MR) image and there are several types of software based on binarization for segmentation of MR head images. We segmented superficial tissues which effect the light propagation in human head from MR images acquired with FATSAT and FIESTA pulse sequences by using region growing algorithm and morphological operation to facilitate the construction of the individual head models for DOT. The pixel intensity distribution of these images has appropriate characteristics to extract the superficial tissues by using algorithm based on binarization. The result of extraction was compared with the extraction from T2-weighted image which is commonly used to extract superficial tissues. The result of extraction from FATSAT or FIESTA image agree well with ground truth determined by manual segmentation.

We present a tool for Monte Carlo simulations of polarized light transport in biological tissue samples. This tool can be adapted to various scenarios thanks to a user interface that allows both complex geometrical structures and different illuminating beam profiles to be generated. By combining spheres, cylinders and half-spaces, the user is able to create highly intricate physical models, with each geometrical element able to be assigned its own optical properties: absorption and scattering coefficients, refractive index and scattering law. The scattering law models currently utilized by the tool are the Mie scattering law and the polarized version of the generalized Henyey-Greenstein scattering law: these models can be customized by modifying the appropriate parameters. A tracing method is used to track the propagating photons and handle the reflection/transmission processes (using the Fresnel relations) at interfaces between two different media. Virtual CCDs coupled with polarizers are used to carry out the imaging of the backscattered and transmitted light. The Mueller matrix of the sample can be obtained by measuring the changes that occur in the polarization states (represented by complex Jones vectors) of the propagating photons. The propagating light's temporal and spatial profiles can also be visualized.

Analytical expressions for the fluence and radiance of the steady-state radiative transfer equation in an infinitely extended and anisotropically scattering medium were derived for different source types. The analytical solutions were compared to Monte Carlo simulations demonstrating an excellent agreement between both models.

Light propagation in semi-infinite turbid media is studied in the steady-state domain by taking into account exact boundary conditions at the probe-medium interface. Monte Carlo simulations, considering different probe geometries were performed. In addition, the influence on determination of the reduced scattering and absorption coefficients is outlined by fitting the diffuse reflectance curves with diffusion theory.

Nine-layered skin tissue model is developed for Monte Carlo simulation of spectral reflectance. Various spectral reflectance curves are generated by taking different values in five input parameters: scattering coefficient, absorption coefficient, anisotropic scattering parameter, refractive index, and layer thickness in each of the nine layers. These curves are then discussed to investigate spectral characteristics corresponding to change of values in the parameters. Using appropriate values in such optical and geometrical parameters, simulated spectra can be produced to agree well with measured spectra. This approach provides a flexible spectral fitting means to measured results and estimation of change in the parameters in skin tissue.

We consider the problem of optical tomographic imaging in a weakly scattering medium in the presence of highly scattering inclusions. The approach is based on the assumption that scattering media consist of weakly and highly scattering regions, whose transport coefficients differ by an order of magnitude. The image reconstruction algorithm is based on the variational framework and employs angularly selective intensity measurements. The methodology is verified by reconstruction of optical and fluorescent parameters from numerically simulated datasets.

We present a diffuse optical tomography (DOT) algorithm for imaging the absorption distribution in a biological tissue using time-domain optical measurements. The time-dependent parabolic simplified spherical polynomials approximation of the radiative transfer equation (the TD-pSP_N model) serves as the forward model. The DOT algorithm is implemented using a nested analysis and design (NAND) method developed for solving constrained optimization problems. Numerical experiments are provided for small geometry media to mimic small animal imaging. In these experiments, the optical absorption coefficient value is varied within typical values found in the near infrared range for biological tissues, including high absorption values. The results show good spatial and quantitative reconstructions and support our TD-pSP_N-based DOT algorithm as an accurate approach to image absorption in biological media.

This paper proposes a perturbation model for time-domain diffuse optical tomography in the flat layer transmission geometry. We derive an analytical representation of the weighting function that models the imaging operator by using the diffusion approximation of the radiative transfer equation and the perturbation theory by Born. To evaluate the weighing function for the flat layer geometry, the Green's function of the diffusion equation for a semi-infinite scattering medium with the Robin boundary condition is used. For time-domain measurement data we use the time-resolved optical projections defined as relative disturbances in the photon fluxes, which are caused by optical inhomogeneities. To demonstrate the efficiency of the proposed model, a numerical experiment was conducted, wherein the rectangular scattering objects with two absorbing inhomogeneities and a randomly inhomogeneous component were reconstructed. Test tomograms are recovered by means of the multiplicative algebraic reconstruction technique modified by us. It is shown that nonstandard interpretation of the time-domain measurement data makes it possible to use different time-gating delays for regularization of the reconstruction procedure. To regularize the solution, we state the reconstruction problem for an augmented system of linear algebraic equations. At the recent stage of study the time-gating delays for regularization are selected empirically.

The proposed image reconstruction method exploits the spectrally dependent absorption properties of biological tissue and quantum dots for recovering the three-dimensional reporter distribution. Only a single light source with macro-illumination needs to be used for the purpose of light emission stimulation and image reconstruction. The light propagation in strongly absorbing tissue is modeled with the simplified spherical harmonics (SPN) equations.

In the context of continuous wave fluorescence-enhanced diffuse optical tomography, we show that the reconstructed fluorescence depends on the local diffusion coefficient and demonstrate that the a priori knowledge of specific optical parameters may lead to the reconstruction of absolute quantification of the fluorophore distribution. In this context, we point out the potentiality of a bimodal instrument coupling functional and morphological information to provide knowledge of the distribution of optical parameters of internal organs. We show some quantitative results on simulated and experimental data on phantoms and conclude suggesting the use of optical parameters atlases to achieve an absolute quantification of fluorophore distribution in real contexts.

Fluorescence diffuse optical tomography (FDOT) based on the total light approach is developed. The continuous wave light is used for excitation in this system. The reconstruction algorithm is based on the total light approach that reconstructs the absorption coefficients increased by the fluorophore. Additionally we propose noise reduction using the algebraic reconstruction technique (ART) incorporating the truncated singular value decomposition (TSVD). Numerical and phantom experiments show that the developed system successfully reconstructs the fluorophore concentration in the biological media, and the ART with TSVD alleviates the influence of noises. In vivo experiment demonstrated that the developed FDOT system localized the fluorescent agent which was concentrated in the cancer transplanted into a kidney in a mouse.

Optical imaging using independent component analysis (OPTICA) and time reversal optical tomography (TROT) approaches are used to detect, locate, and obtain cross-section images of two tumor pieces inside a model human breast assembled using ex vivo human breast tissues and configured as a semi-cylindrical slab of uniform thickness. The experimental arrangement realized a multi-source probing scheme to illuminate an end face (source plane) of the slab sample using 750 nm, 800 nm and 830 nm beams of laser light. A multi-detector signal acquisition scheme measured transmitted light intensity distribution on the other end face (detection plane). This combined multi-source probing and multi-detector sensing approach culminated in multiple spatial and angular views of the sample necessary for target localization. The perturbations in light intensity distribution in the detection plane were analyzed using both the OPTICA and the TROT approaches to obtain locations of the tumor pieces. A back-projection technique with OPTICA provided cross-section images and estimates of cross section of the targets within the sample. The estimated locations and dimensions of targets are in good agreement with the results of a corroborating magnetic resonance imaging experiment and known values.

An imager for optical tomography was designed based on a detector with 128×128 single-photon pixels that included a bank of 32 time-to-digital converters. Due to the high spatial resolution and the possibility of performing time resolved measurements, a new contact-less setup has been conceived in which scanning of the object is not necessary. This enables one to perform high-resolution optical tomography with much higher acquisition rate, which is fundamental in clinical applications. The setup has a resolution of 97ps and operates with a laser source with an average power of 3mW. This new imaging system generated a high amount of data that could not be processed by established methods, therefore new concepts and algorithms were developed to take full advantage of it. Images were generated using a new reconstruction algorithm that combined general inverse problem methods with Fourier transforms in order to reduce the complexity of the problem. Simulations show that the potential resolution of the new setup is in the order of millimeters. Experiments have been performed to confirm this potential. Images derived from the measurements demonstrate that we have already reached a resolution of 5mm.

We present a photoacoustic measurement system based on semiconductor lasers for blood oxygenation measurements. It permits to use four different optical wavelengths (650nm, 808nm, 850nm, 905nm) to generate photoacoustic signals. As the optical extinction coefficient of oxygenated hemoglobin and deoxygenated hemoglobin is different at specific wavelengths, a blood oxygenation measurement by a multi-wavelength photoacoustic laser system is feasible. Especially at 650nm, the clear difference between the extinction coefficients of the two hemoglobin derivates permits to determine the blood oxygenation in combination with other near infrared wavelengths. A linear model based on tabulated values of extinction coefficients for fully oxygenated and fully deoxygenated hemoglobin is presented. We used heparin stabilized whole porcine blood samples to model the optical behavior of human blood, as the optical absorption behavior of porcine hemoglobin does not differ significantly from human hemoglobin. To determine the real oxygen saturation values of the blood samples, we measured the partial oxygen pressure with an IRMA Trupoint Blood Analysis System. The oxygen saturation values were calculated from a dissociation curve for porcine blood. The results of the photoacoustic measurement are in qualitatively good agreement with the predicted linear model. Further, we analyze the abilities and the limitations of quantitative oxygenation measurements.

We propose a system for time-domain diffuse optical spectroscopy extending up to 1300 nm based on a supercontinuum source and time-correlated single photon counting detection. The system was validated on liquid phantoms demonstrating a good linearity up to an absorption coefficient of 2.0 cm^-1. Preliminary measurements on collagen powder reveal an important absorption peak around 1200 nm. Feasibility of in vivo diffuse optical spectroscopy on the female breast is demonstrated up to 1200 nm at an interfiber distance of 2 cm.

The method proposed here allows to perform a selection of a well defined subsurface volume in a turbid medium allowing SNR enhancement for functional imaging of the cortex. The principle consists in sequentially probing the biological tissue with light polarized linearly or circularly. The method and preliminary results obtained on phantoms are presented.

The analysis of diffuse reflectance spectra of skin using a multi-layered model is applied to a variety of fields. Skin has complex multi-layered structure and the penetration depth of the detected light depends upon the wavelength dependence of the optical properties of each layer. It is important to consider the wavelength dependence of the penetration depth of the detected light in order to analyse the diffuse reflectance spectra of the skin. In this study, the photon vanishment in multi-layered model is calculated by Monte Carlo simulation to estimate the contribution of absorption in each layer to diffuse reflectance spectra. We analyse the influence of the anatomical structure of skin and the geometry of detection system on the contribution of each layer to diffuse reflectance spectra. The results are compared with the reflectance spectra of human skin and lip of four volunteers measured with a fibre probe and an integrating sphere. The proposed models of skin and lip can reasonably represent the difference in the spectra between the fibre probe and the integrating sphere. The change in penetration depth of detected light caused by the detection systems depends upon wavelength and it causes the differences in the diffuse reflectance spectra.

Near-infrared (NIR) topography has been applied to the measurement of brain activation. However the position resolution of optical topography is not sufficient to measure focal brain activation. Since the localization of the brain activation in visual cortex depends on the visual stimuli position, it is difficult to resolve the localized brain activation in the visual cortex by NIR topography. In this study, we measured the localised brain activation evoked by visual stimulation to evaluate the position resolution of NIR topography with the high-density probe arrangement. The topographic image is obtained without solving inverse problem to investigate the effect of the high-density probe arrangement on improvement of the position resolution of NIR topography. When the brain activations evoked by the broad visual stimuli such as the whole checker boards, the topographic image measured with the single-density arrangement is almost the same as that with the double-density arrangement. The double-density arrangement effectively improves the topographic image when the brain activations were evoked by the localized visual stimuli such as the fanshaped checker boards.

A new method for cancelling the skin blood flow in functional near-infrared spectroscopy (fNIRS) is proposed to improve the measurement accuracy of oxygen consumption in a brain tissue. We proposed to use two kinds of cancellation signals. One is a sharing aperture approach which uses cancellation signals detected at apertures for irradiating the light. Another one is an additional aperture approach which uses cancellation signals detected at the midpoint between the irradiation and detection aperture in conventional measurement. We further applied an equilateral-triangular probe arrangement to our method. For the equilateral-triangular probe arrangement, the cancellation signal of the sharing aperture approach is detected at apex, and the cancellation signal of the additional aperture approach is detected at the median point of the equilateral-triangular. Simulation and experiments with a phantom were performed. Simulation results show that the proposed method effectively detected the influence of the near-surface absorption change, which depends on its position and size, by automatically selecting the two kinds of cancellation signal.

In near-infrared topography, the topographic images of the brain activation considerably depend on the relative position between the probe arrangement and brain activation. The variance of topographic image due to the relative position between the brain activation and the probe arrangement is evaluated by the phantom experiment and simulation. We examined five types of probe arrangements. The variation of the topographic images measured by 15-mm probe arrangements is considerably improved in comparison with the image measured by the 30-mm probe arrangements. The images are almost independent of the relative position in case where the diameter of the brain activation is greater than 30mm.

Breast density is a major risk factor for developing breast cancer. Non-invasive assessment of breast density was performed by means of time-resolved 7-wavelength (635-1060 nm) optical mammography. Good correlation was achieved between mammographic density and optically derived indexes in a clinical study that is presently ongoing and that has involved 63 subjects up to now.

We use near infrared spectroscopy (NIRS) for the non-invasive assessment of calf oxygenation during a new walking protocol in healthy subjects of different fitness levels. The protocol increases the exercise power by an increase of the skew rather than speed, and the incremental power steps are intermitted by a 30 s rest which serves for blood sampling. The NIRS measurement parameter of tissue oxygenation are discussed, and a high correlation of the oxygen saturation (tissue oxygenation index) difference between exercise and rest period with exercise power is observed. This difference parameter can be interpreted as strongly linked to blood flow rather than oxygenation. This finding is supported by comparison with spirometry data. The effect of training is discussed. The exercise protocol is suited for testing unfit, or older subjects and the data discussed here servers as a test for a larger trial with heart clinic patients.

A polarization-sensitive Monte Carlo model is used to investigate differently polarized light illuminations on their degree of polarization (DOP) depth evolution in a semi-infinite scattering medium. The three-dimensional simulations show that circular polarized light maintains its initial polarization state longer than elliptical or linear polarized light. It was revealed that elliptical polarization can be tuned so that its DOP depth evolution can be precisely chosen between the penetration depths of linearly and circularly polarized light.

We propose an algorithm based on a two-layer optical model to quantify CBF from dynamic contrast-enhanced near-infrared data acquired with a two-channel broadband system. The key novel aspect of the algorithm is the ability to separate the contrast agent concentration, indocyanine green (ICG), in extracerebral (EC) tissue and cerebral cortex by representing the (EC) tissue as the top optical layer and the brain as the bottom optical layer. Experiments were conducted on a juvenile pig model. Broadband near-infrared spectra were acquired at source-detectors distances of 1 and 3 cm. The first step of the algorithm was to find the baseline optical properties of the layers by a multi-parameter wavelength-dependent data fit of a photon diffusion equation solution for a two-layer media. The second step was to use the baseline optical properties to separate the ICG concentration time course in brain from the ICG time course in EC tissue. The final step was to calculate CBF from the cerebral ICG time course. The resulting CBF measurements were in good agreement with concurrent measurements acquired by computed tomography, which a difference of 20%.

Steps are presented towards the development of a new bioluminescence tomography (BLT) imaging system for in vivo small animal studies. A 2-mirror-based multi-view data collection scheme is investigated in conjunction with multi-spectral imaging, leading to the production of 3D volumetric maps of molecular source distributions in simulation and in physical phantom studies by way of a finite element model (FEM) based reconstruction method. A proof of concept is subsequently demonstrated showing a full work flow from data acquisition to 3D reconstruction. Results suggest that the multi-view mirror-based approach represents a strong improvement over standard single-view methods, with improvements of up to 58% in source localisation accuracy being observed for deep sources.

Although near infrared spectroscopy (NIRS) is now widely used both in emerging clinical techniques and in cognitive neuroscience, the development of the apparatuses and signal processing methods for these applications is still a hot research topic. The main unresolved problem in functional NIRS is the separation of functional signals from the contaminations by systemic and local physiological fluctuations. This problem was approached by using various signal processing methods, including blind signal separation techniques. In particular, principal component analysis (PCA) and independent component analysis (ICA) were applied to the data acquired at the same wavelength and at multiple sites on the human or animal heads during functional activation. These signal processing procedures resulted in a number of principal or independent components that could be attributed to functional activity but their physiological meaning remained unknown. On the other hand, the best physiological specificity is provided by broadband NIRS. Also, a comparison with functional magnetic resonance imaging (fMRI) allows determining the spatial origin of fNIRS signals. In this study we applied PCA and ICA to broadband NIRS data to distill the components correlating with the breath hold activation paradigm and compared them with the simultaneously acquired fMRI signals. Breath holding was used because it generates blood carbon dioxide (CO2) which increases the blood-oxygen-level-dependent (BOLD) signal as CO2 acts as a cerebral vasodilator. Vasodilation causes increased cerebral blood flow which washes deoxyhaemoglobin out of the cerebral capillary bed thus increasing both the cerebral blood volume and oxygenation. Although the original signals were quite diverse, we found very few different components which corresponded to fMRI signals at different locations in the brain and to different physiological chromophores.

We present a combination of two CW methods, measurement of the spatially resolved reflectance and of the total reflectance, for determination of the reduced scattering and absorption coefficients of turbid media. The results are compared with independent methods and show excellent agreement.

In this paper we present two-dimensional phantom measurements of fluorescence light distribution in the frequency domain and reconstruction of three-dimensional fluorophore distribution. An experimental set-up was built up with two dimensional laser scanning, intensity modulation with frequencies up to 1 GHz, and two-dimensional imaging of modulated fluorescence light. Stable phantoms were developed simulating mammary tissue to perform measurements in a backscattering geometry for a variety of cylindrical fluorescence sources with different diameters, fluorophore concentrations, and surface distances at different modulation frequencies. At first calculated fluorescence light distributions from Monte-Carlo simulations was compared to measured data. In a second step from tomographic data sets of calculated fluorescent light, three-dimensional tomographic reconstructions of fluorophore distribution were performed. Finally three-dimensional tomographic reconstructions of fluorophore distribution were performed from tomographic fluorescence measurements. We found good concurrence between measured and calculated fluorescence distribution. Synthetic and real tomographic reconstruction showed good localization but underestimated the depth of fluorophore distribution.

Fluorescence tomography seeks to image an inaccessible fluorophore distribution inside an object like a small animal by injecting light at the boundary and measuring the light emitted by the fluorophore. Optical parameters (e.g. the conversion efficiency or the fluorescence life-time) of certain fluorophores depend on physiologically interesting quantities like the pH value or the oxygen concentration in the tissue, which allows functional rather than just anatomical imaging. To reconstruct the concentration and the life-time from the boundary measurements, a nonlinear inverse problem has to be solved. It is, however, difficult to estimate the uncertainty of the reconstructed parameters in case of iterative algorithms and a large number of degrees of freedom. Uncertainties in fluorescence tomography applications arise from model inaccuracies, discretization errors, data noise and a priori errors. Thus, a Markov chain Monte Carlo method (MCMC) was used to consider all these uncertainty factors exploiting Bayesian formulation of conditional probabilities. A 2-D simulation experiment was carried out for a circular object with two inclusions. Both inclusions had a 2-D Gaussian distribution of the concentration and constant life-time inside of a representative area of the inclusion. Forward calculations were done with the diffusion approximation of Boltzmann's transport equation. The reconstruction results show that the percent estimation error of the lifetime parameter is by a factor of approximately 10 lower than that of the concentration. This finding suggests that lifetime imaging may provide more accurate information than concentration imaging only. The results must be interpreted with caution, however, because the chosen simulation setup represents a special case and a more detailed analysis remains to be done in future to clarify if the findings can be generalized.

Fluorescence tomography aims at the reconstruction of the concentration and life-time of fluorescent inclusions from boundary measurements of light emitted. The underlying ill-posed problem is often solved with gradient descent of Gauss-Newton methods, for example. Unfortunately, these approaches don't allow to assess the quality of the reconstruction (e.g. the variance and covariance of the parameters) and also require the tuning of regularization parameters. We intend to mitigate this drawback by the application of topological derivatives and Markov-chain Monte-Carlo (MCMC) methods for solving the inverse problem. This submission focuses on the topological derivative, which is used for the initialization of the MCMC code. The basic idea is to probe every location inside the domain with an infinitely small fluorescent ball and to estimate the effect of such a perturbation on the residual, which is the difference of the theoretically predicted data to the true measurement. Obviously, the reconstructed inclusions should be placed at locations for which the topological derivative is significantly negative, i.e. where the residual decreases. Previous results show that usual first-order approximations deteriorates for probe inclusions close to the boundary. This seems to be a particular feature of certain inverse problems such as fluorescence tomography or electrical impedance tomography. Fortunately this flaw may be corrected using a few higher-order terms which may be explicitly determined With this extension the topological derivative can be utilized as a one-step method for the determination of the number of inclusions and their approximate locations. This outcome is used as initialization for the MCMC algorithm.

In this work, optical propagation through turbid media is analyzed by FDTD simulation. In particular, the method is applied to biological tissues. Continuous light propagation in turbid media has been widely studied, but pulsed light propagation has received less interest due to its complexity. Therefore, in this work we focus on pulsed light. FDTD method is applied to several media with optical parameters in the typical range of those observed in biological tissues. We perform an analysis of the variations of pulsed light propagation as a function of the scatterers characteristics (namely size, concentration, and optical contrast). The results are compared with those obtained by the use of the diffusion approximation. The potential of the FDTD method over the diffusion model is given by its high accuracy, its capacity to perform time-resolved simulations, and the fact that it carries all the information about the phase and coherence of the wavefront. The results of this work can be applied to a wide range of areas of interest like the time-resolved study of ultrashort light pulses propagation, the optimization of optical penetration depth, the coherence properties of pulsed light, and the effect of modified wavefronts in light propagation.

NIRFAST is open source software for near infrared (NIR) imaging using finite element method for modeling light diffusion tissue. Recently, we integrated an add-on to NIRFAST based on boundary-element method (BEM) solution to the diffusion equation. This toolbox requires only surface discretization of the imaging domain as opposed to volume meshing, geared towards 3D NIR spectroscopy. The software is Matlab-based and provides a framework for surface meshing, forward model, reconstruction and data and solution visualization capabilities as well as ability to run in parallel environments using OpenMP standard. This was validated in simulations, experiments and applied to in-vivo clinical data and was made open-source for the near infrared imaging community.

A boundary element method with dual reciprocity method (BEM-DRM) was used to model fluorescence in tissue using coupled diffusion equations in 3D. This method eliminates the need for node connectivity in a volume mesh of arbitrary shapes, requiring instead, a surface mesh with interior points to model the fluorescence source in 3D. Results using BEM-DRM show agreement with data from open source finite-element based software package NIRFAST⁷ with mean error difference of 0.08 for optimally chosen support parameter for radial basis functions used.

In recent years optical methods became increasingly popular for pre-clinical research and small animal imaging. One main field in biomedical optics research is the diffuse optical tomography (DOT). Many new systems were invented for small animal imaging and breast cancer detection. In combination with the progress in the development of optical markers, optical detectors and near infrared light sources, these new systems have become a formidable source of information. Most of the systems detect the transmitted light which passes through an object and one observes the intensity variations on the detector side. The biggest challenge for all diffuse optical tomography systems is the enormous scattering of light in tissues and tissue-like phantoms resulting in loss of image information. Many systems work with contact gels and optical fibers that have direct contact with the object to neglect the light path between surface and detector. Highly developed mathematic models and reconstruction algorithms based on FEM and Monte Carlo simulations describe the light transport inside tissues and determine differences in absorption and scattering coefficients inside. The proposed method allows a more exact description of the orientation of surface elements from semi-transparent objects towards the detector. Using Polarization Difference Imaging (PDI) in combination with structured light 3D-scanning, it is possible to separate information from the surface from that of the subsurface. Thus, the actual surface shape can be determined. Furthermore, overlaying byproducts caused by inter-reflections and multiple scattering can be filtered from the basic image information with this method. To enhance the image quality, the intensity dispersion between surface and camera is calculated and the creation of 3D-FEM-meshes simplified.