Singular value decomposition based computationally efficient algorithm for rapid dynamic near-infrared diffuse optical tomography

Purpose: A computationally efficient algorithm (linear iterative type) based on singular value decomposition (SVD) of the Jacobian has been developed that can be used in rapid dynamic near-infrared (NIR) diffuse optical tomography. Methods: Numerical and experimental studies have been conducted to prove the computational efficacy of this SVD-based algorithm over conventional optical image reconstruction algorithms. Results: These studies indicate that the performance of linear iterative algorithms in terms of contrast recovery (quantitation of optical images) is better compared to nonlinear iterative (conventional) algorithms, provided the initial guess is close to the actual solution. The nonlinear algorithms can provide better quality images compared to the linear iterative type algorithms. Moreover, the analytical and numerical equivalence of the SVD-based algorithm to linear iterative algorithms was also established as a part of this work. It is also demonstrated that the SVD-based image reconstruction typically requires O(NN2) operations per iteration, as contrasted with linear and nonlinear iterative methods that, respectively, requir O(NN3) and O(NN6) operations, with ``NN'' being the number of unknown parameters in the optical image reconstruction procedure. Conclusions: This SVD-based computationally efficient algorithm can make the integration of image reconstruction procedure with the data acquisition feasible, in turn making the rapid dynamic NIR tomography viable in the clinic to continuously monitor hemodynamic changes in the tissue pathophysiology.

Convergence analysis of the Newton algorithm and a pseudo-time marching scheme for diffuse correlation tomography

We propose a self-regularized pseudo-time marching scheme to solve the ill-posed, nonlinear inverse problem associated with diffuse propagation of coherent light in a tissuelike object. In particular, in the context of diffuse correlation tomography (DCT), we consider the recovery of mechanical property distributions from partial and noisy boundary measurements of light intensity autocorrelation. We prove the existence of a minimizer for the Newton algorithm after establishing the existence of weak solutions for the forward equation of light amplitude autocorrelation and its Frechet derivative and adjoint. The asymptotic stability of the solution of the ordinary differential equation obtained through the introduction of the pseudo-time is also analyzed. We show that the asymptotic solution obtained through the pseudo-time marching converges to that optimal solution provided the Hessian of the forward equation is positive definite in the neighborhood of optimal solution. The superior noise tolerance and regularization-insensitive nature of pseudo-dynamic strategy are proved through numerical simulations in the context of both DCT and diffuse optical tomography. (C) 2010 Optical Society of America.

Performance Analysis of Reconstruction Techniques for Frequency-Domain Optical-Coherence Tomography

We address the issue of noise robustness of reconstruction techniques for frequency-domain optical-coherence tomography (FDOCT). We consider three reconstruction techniques: Fourier, iterative phase recovery, and cepstral techniques. We characterize the reconstructions in terms of their statistical bias and variance and obtain approximate analytical expressions under the assumption of small noise. We also perform Monte Carlo analyses and show that the experimental results are in agreement with the theoretical predictions. It turns out that the iterative and cepstral techniques yield reconstructions with a smaller bias than the Fourier method. The three techniques, however, have identical variance profiles, and their consistency increases linearly as a function of the signal-to-noise ratio.

Clinical application of biomarkers in prostate cancer in men with metabolic syndrome project: Prostate Specific Membrane Antigen (PSMA) Positron Emission Tomography (PET) in diagnosing localised prostate cancer

Localised prostate cancer is a heterogenous disease and a multi-modal approach is required to accurately diagnose and stage the disease. Whilst the use of magnetic resonance imaging (MRI) has become more common, small volume and multi-focal disease are oft en diffi cult to characterise. Prostate specifi c membrane antigen is a cell surface protein, which is expressed in nearly all prostate cancer cells. Its expression is signifi cantly higher in high grade prostate cancer cells. In this study, we compare multi-parametric magnetic resonance imaging and 68-Gallinium-PSMA PET with whole-mount pathology of the prostate to evaluate the applicability of multiparameteric (MP) MRI and 68Ga-PSMA PET in detecting and locating tumour foci in patients with localised prostate cancer.

Modern computed tomography techniques in stroke management

Technological development of fast multi-sectional, helical computed tomography (CT) scanners has allowed computed tomography perfusion (CTp) and angiography (CTA) in evaluating acute ischemic stroke. This study focuses on new multidetector computed tomography techniques, namely whole-brain and first-pass CT perfusion plus CTA of carotid arteries. Whole-brain CTp data is acquired during slow infusion of contrast material to achieve constant contrast concentration in the cerebral vasculature. From these data quantitative maps are constructed of perfused cerebral blood volume (pCBV). The probability curve of cerebral infarction as a function of normalized pCBV was determined in patients with acute ischemic stroke. Normalized pCBV, expressed as a percentage of contralateral normal brain pCBV, was determined in the infarction core and in regions just inside and outside the boundary between infarcted and noninfarcted brain. Corresponding probabilities of infarction were 0.99, 0.96, and 0.11, R² was 0.73, and differences in perfusion between core and inner and outer bands were highly significant. Thus a probability of infarction curve can help predict the likelihood of infarction as a function of percentage normalized pCBV. First-pass CT perfusion is based on continuous cine imaging over a selected brain area during a bolus injection of contrast. During its first passage, contrast material compartmentalizes in the intravascular space, resulting in transient tissue enhancement. Functional maps such as cerebral blood flow (CBF), and volume (CBV), and mean transit time (MTT) are then constructed. We compared the effects of three different iodine concentrations (300, 350, or 400 mg/mL) on peak enhancement of normal brain tissue and artery and vein, stratified by region-of-interest (ROI) location, in 102 patients within 3 hours of stroke onset. A monotonic increasing peak opacification was evident at all ROI locations, suggesting that CTp evaluation of patients with acute stroke is best performed with the highest available concentration of contrast agent. In another study we investigated whether lesion volumes on CBV, CBF, and MTT maps within 3 hours of stroke onset predict final infarct volume, and whether all these parameters are needed for triage to intravenous recombinant tissue plasminogen activator (IV-rtPA). The effect of IV-rtPA on the affected brain by measuring salvaged tissue volume in patients receiving IV-rtPA and in controls was investigated also. CBV lesion volume did not necessarily represent dead tissue. MTT lesion volume alone can serve to identify the upper size limit of the abnormally perfused brain, and those with IV-rtPA salvaged more brain than did controls. Carotid CTA was compared with carotid DSA in grading of stenosis in patients with stroke symptoms. In CTA, the grade of stenosis was determined by means of axial source and maximum intensity projection (MIP) images as well as a semiautomatic vessel analysis. CTA provides an adequate, less invasive alternative to conventional DSA, although tending to underestimate clinically relevant grades of stenosis.

A FEM-Based Forward Solver for Studying the Forward Problem of Electrical Impedance Tomography (EIT) with A Practical Biological Phantom

A Finite Element Method based forward solver is developed for solving the forward problem of a 2D-Electrical Impedance Tomography. The Method of Weighted Residual technique with a Galerkin approach is used for the FEM formulation of EIT forward problem. The algorithm is written in MatLAB7.0 and the forward problem is studied with a practical biological phantom developed. EIT governing equation is numerically solved to calculate the surface potentials at the phantom boundary for a uniform conductivity. An EIT-phantom is developed with an array of 16 electrodes placed on the inner surface of the phantom tank filled with KCl solution. A sinusoidal current is injected through the current electrodes and the differential potentials across the voltage electrodes are measured. Measured data is compared with the differential potential calculated for known current and solution conductivity. Comparing measured voltage with the calculated data it is attempted to find the sources of errors to improve data quality for better image reconstruction.

Single-resolution and multiresolution extended-Kalman-filter-based reconstruction approaches to optical refraction tomography

The problem of reconstruction of a refractive-index distribution (RID) in optical refraction tomography (ORT) with optical path-length difference (OPD) data is solved using two adaptive-estimation-based extended-Kalman-filter (EKF) approaches. First, a basic single-resolution EKF (SR-EKF) is applied to a state variable model describing the tomographic process, to estimate the RID of an optically transparent refracting object from noisy OPD data. The initialization of the biases and covariances corresponding to the state and measurement noise is discussed. The state and measurement noise biases and covariances are adaptively estimated. An EKF is then applied to the wavelet-transformed state variable model to yield a wavelet-based multiresolution EKF (MR-EKF) solution approach. To numerically validate the adaptive EKF approaches, we evaluate them with benchmark studies of standard stationary cases, where comparative results with commonly used efficient deterministic approaches can be obtained. Detailed reconstruction studies for the SR-EKF and two versions of the MR-EKF (with Haar and Daubechies-4 wavelets) compare well with those obtained from a typically used variant of the (deterministic) algebraic reconstruction technique, the average correction per projection method, thus establishing the capability of the EKF for ORT. To the best of our knowledge, the present work contains unique reconstruction studies encompassing the use of EKF for ORT in single-resolution and multiresolution formulations, and also in the use of adaptive estimation of the EKF's noise covariances. (C) 2010 Optical Society of America

Quantitative photoacoustic tomography from boundary pressure measurements: noniterative recovery of optical absorption coefficient from the reconstructed absorbed energy map

We describe a noniterative method for recovering optical absorption coefficient distribution from the absorbed energy map reconstructed using simulated and noisy boundary pressure measurements. The source reconstruction problem is first solved for the absorbed energy map corresponding to single- and multiple-source illuminations from the side of the imaging plane. It is shown that the absorbed energy map and the absorption coefficient distribution, recovered from the single-source illumination with a large variation in photon flux distribution, have signal-to-noise ratios comparable to those of the reconstructed parameters from a more uniform photon density distribution corresponding to multiple-source illuminations. The absorbed energy map is input as absorption coefficient times photon flux in the time-independent diffusion equation (DE) governing photon transport to recover the photon flux in a single step. The recovered photon flux is used to compute the optical absorption coefficient distribution from the absorbed energy map. In the absence of experimental data, we obtain the boundary measurements through Monte Carlo simulations, and we attempt to address the possible limitations of the DE model in the overall reconstruction procedure.

Seismic Tomography and Earthquake Mechanism Beneath the Central Fennoscandian Shield

The aim of this thesis was to study the seismic tomography structure of the earth s crust together with earthquake distribution and mechanism beneath the central Fennoscandian Shield, mainly in southern and central Finland. The earthquake foci and some fault plane solutions are correlated with 3-D images of the velocity tomography. The results are discussed in relation to the stress field of the Shield and with other geophysical, e.g. geomagnetic, gravimetric, tectonic, and anisotropy studies of the Shield. The earthquake data of the Fennoscandian Shield has been extracted from the Nordic earthquake parameter data base which was founded at the time of inception of the earthquake catalogue for northern Europe. Eight earlier earthquake source mechanisms are included in a pilot study on creating a novel technique for calculating an earthquake fault plane solution. Altogether, eleven source mechanisms of shallow, weak earthquakes are related in the 3-D tomography model to trace stresses of the crust in southern and central Finland. The earthquakes in the eastern part of the Fennoscandian Shield represent low-active, intraplate seismicity. Earthquake mechanisms with NW-SE oriented horizontal compression confirm that the dominant stress field originates from the ridge-push force in the North Atlantic Ocean. Earthquakes accumulate in coastal areas, in intersections of tectonic lineaments, in main fault zones or are bordered by fault lines. The majority of Fennoscandian earthquakes concentrate on the south-western Shield in southern Norway and Sweden. Onwards, epicentres spread via the ridge of the Shield along the west-coast of the Gulf of Bothnia northwards along the Tornio River - Finnmark fault system to the Barents Sea, and branch out north-eastwards via the Kuusamo region to the White Sea Kola Peninsula faults. The local seismic tomographic method was applied to find the terrane distribution within the central parts of the Shield the Svecofennian Orogen. From 300 local explosions a total of 19765 crustal Pg- and Sg-wave arrival times were inverted to create independent 3-D Vp and Vs tomographic models, from which the Vp/Vs ratio was calculated. The 3-D structure of the crust is presented as a P-wave and for the first time as an S-wave velocity model, and also as a Vp/Vs-ratio model of the SVEKALAPKO area that covers 700x800 km2 in southern and central Finland. Also, some P-wave Moho-reflection data was interpolated to image the relief of the crust-mantle boundary (i.e. Moho). In the tomography model, the seismic velocities vary smoothly. The lateral variations are larger for Vp (dVp =0.7 km/s) than for Vs (dVs =0.4 km/s). The Vp/Vs ratio varies spatially more distinctly than P- and S-wave velocities, usually from 1.70 to 1.74 in the upper crust and from 1.72 to 1.78 in the lower crust. Schist belts and their continuations at depth are associated with lower velocities and lower Vp/Vs ratios than in the granitoid areas. The tomography modelling suggests that the Svecofennian Orogen was accreted from crustal blocks ranging in size from 100x100 km2 to 200x200 km2 in cross-sectional area. The intervening sedimentary belts have ca. 0.2 km/s lower P- and S-wave velocities and ca. 0.04 lower Vp/Vs ratios. Thus, the tomographic model supports the concept that the thick Svecofennian crust was accreted from several crustal terranes, some hidden, and that the crust was later modified by intra- and underplating. In conclusion, as a novel approach the earthquake focal mechanism and focal depth distribution is discussed in relation to the 3-D tomography model. The schist belts and the transformation zones between the high- and low-velocity anomaly blocks are characterized by deeper earthquakes than the granitoid areas where shallow events dominate. Although only a few focal mechanisms were solved for southern Finland, there is a trend towards strike-slip and oblique strike-slip movements inside schist areas. The normal dip-slip type earthquakes are typical in the seismically active Kuusamo district in the NE edge of the SVEKALAPKO area, where the Archean crust is ca. 15-20 km thinner than the Proterozoic Svecofennian crust. Two near vertical dip-slip mechanism earthquakes occurred in the NE-SW junction between the Central Finland Granitoid Complex and the Vyborg rapakivi batholith, where high Vp/Vs-ratio deep-set intrusion splits the southern Finland schist belt into two parts in the tomography model.

A Simple Instrumentation Calibration Technique for Electrical Impedance Tomography (EIT) Using A 16-Electrode Phantom

A simple analog instrumentation for Electrical Impedance Tomography is developed and calibrated using the practical phantoms. A constant current injector consisting of a modified Howland voltage controlled current source fed by a voltage controlled oscillator is developed to inject a constant current to the phantom boundary. An instrumentation amplifier, 50 Hz notch filter and a narrow band pass filter are developed and used for signal conditioning. Practical biological phantoms are developed and the forward problem is studied to calibrate the EIT-instrumentation. An array of sixteen stainless steel electrodes is developed and placed inside the phantom tank filled with KCl solution. 1 mA, 50 kHz sinusoidal current is injected at the phantom boundary using adjacent current injection protocol. The differential potentials developed at the voltage electrodes are measured for sixteen current injections. Differential voltage signal is passed through an instrumentation amplifier and a filtering block and measured by a digital multimeter. A forward solver is developed using Finite Element Method in MATLAB7.0 for solving the EIT governing equation. Differential potentials are numerically calculated using the forward solver with a simulated current and bathing solution conductivity. Measured potential data is compared with the differential potentials calculated for calibrating the instrumentation to acquire the voltage data suitable for better image reconstruction.

A Study of Practical Biological Phantoms with Simple Instrumentation for Electrical Impedance Tomography (EIT)

16-electrode phantoms are developed and studied with a simple instrumentation developed for Electrical Impedance Tomography. An analog instrumentation is developed with a sinusoidal current generator and signal conditioner circuit. Current generator is developed withmodified Howland constant current source fed by a voltage controlled oscillator and the signal conditioner circuit consisting of an instrumentation amplifier and a narrow band pass filter. Electronic hardware is connected to the electrodes through a DIP switch based multiplexer module. Phantoms with different electrode size and position are developed and the EIT forward problem is studied using the forward solver. A low frequency low magnitude sinusoidal current is injected to the surface electrodes surrounding the phantom boundary and the differential potential is measured by a digital multimeter. Comparing measured potential with the simulated data it is intended to reduce the measurement error and an optimum phantom geometry is suggested. Result shows that the common mode electrode reduces the common mode error of the EIT electronics and reduces the error potential in the measured data. Differential potential is reduced up to 67 mV at the voltage electrode pair opposite to the current electrodes. Offset potential is measured and subtracted from the measured data for further correction. It is noticed that the potential data pattern depends on the electrode width and the optimum electrode width is suggested. It is also observed that measured potential becomes acceptable with a 20 mm solution column above and below the electrode array level.

Image reconstruction by inhomogeneous diffusion for positron emission tomography

In positron emission tomography (PET), image reconstruction is a demanding problem. Since, PET image reconstruction is an ill-posed inverse problem, new methodologies need to be developed. Although previous studies show that incorporation of spatial and median priors improves the image quality, the image artifacts such as over-smoothing and streaking are evident in the reconstructed image. In this work, we use a simple, yet powerful technique to tackle the PET image reconstruction problem. Proposed technique is based on the integration of Bayesian approach with that of finite impulse response (FIR) filter. A FIR filter is designed whose coefficients are determined based on the surface diffusion model. The resulting reconstructed image is iteratively filtered and fed back to obtain the new estimate. Experiments are performed on a simulated PET system. The results show that the proposed approach is better than recently proposed MRP algorithm in terms of image quality and normalized mean square error.

Approximation of Internal Refractive Index Variation Improves Image Guided Diffuse Optical Tomography of Breast

Effective usage of image guidance by incorporating the refractive index (RI) variation in computational modeling of light propagation in tissue is investigated to assess its impact on optical-property estimation. With the aid of realistic patient breast three-dimensional models, the variation in RI for different regions of tissue under investigation is shown to influence the estimation of optical properties in image-guided diffuse optical tomography (IG-DOT) using numerical simulations. It is also shown that by assuming identical RI for all regions of tissue would lead to erroneous estimation of optical properties. The a priori knowledge of the RI for the segmented regions of tissue in IG-DOT, which is difficult to obtain for the in vivo cases, leads to more accurate estimates of optical properties. Even inclusion of approximated RI values, obtained from the literature, for the regions of tissue resulted in better estimates of optical properties, with values comparable to that of having the correct knowledge of RI for different regions of tissue.

A Feature-Based Solution to Forward Problem in Electrical Capacitance Tomography of Conductive Materials

A new feature-based technique is introduced to solve the nonlinear forward problem (FP) of the electrical capacitance tomography with the target application of monitoring the metal fill profile in the lost foam casting process. The new technique is based on combining a linear solution to the FP and a correction factor (CF). The CF is estimated using an artificial neural network (ANN) trained using key features extracted from the metal distribution. The CF adjusts the linear solution of the FP to account for the nonlinear effects caused by the shielding effects of the metal. This approach shows promising results and avoids the curse of dimensionality through the use of features and not the actual metal distribution to train the ANN. The ANN is trained using nine features extracted from the metal distributions as input. The expected sensors readings are generated using ANSYS software. The performance of the ANN for the training and testing data was satisfactory, with an average root-mean-square error equal to 2.2%.