Made available in DSpace on 2014-10-09T12:41:29Z (GMT). No. of bitstreams: 0 / Made available in DSpace on 2014-10-09T14:03:18Z (GMT). No. of bitstreams: 0 / Tese (Doutoramento) / IPEN/T / Instituto de Pesquisas Energeticas e Nucleares - IPEN-CNEN/SP

Made available in DSpace on 2014-10-09T12:41:29Z (GMT). No. of bitstreams: 0 / Made available in DSpace on 2014-10-09T14:03:18Z (GMT). No. of bitstreams: 0 / Neste trabalho, foi investigado o processo de crescimento de fibras monocristalinas (FMc) para aplicação em sistemas laser. Para o aperfeiçoamento na fabricação de FMc de fluoretos, foi projetada e construída uma nova câmara de crescimento para um forno comercial de micro-pulling down (μ-PD), permitindo um rígido controle da atmosfera de processamento, (sob vácuo, fluxo e atmosferas estáticas). Paralelamente, foi investigado o processo de crescimento de FMc de molibdatos duplos de terras raras, sendo crescidas e caracterizadas fibras puras e dopadas com Nd3+ do composto LiLa(MoO4)2 (LLM) com concentrações na faixa de 0,5 a 10mol%. A câmara de crescimento projetada para o controle de atmosfera foi avaliada em diversas condições de operação. Em particular, a mesma foi testada com o puxamento de fibras de LiF, sob atmosfera de CF4, para observação da sua eficiência no controle da atmosfera de crescimento. Foram obtidas FMc de LLM, homogêneas e transparentes; nas fibras puras foi observada a presença de facetas, entretanto, a adequação dos parâmetros de crescimento e a adição de dopantes permitiu a redução significativa destes defeitos. A difração de raios-x mostrou a cristalização no grupo espacial I41/a; medidas de tomografia por coerência ótica permitiram a detecção de centros de espalhamento em regiões onde ocorreram instabilidades no processo de crescimento. Foi possível observar que o coeficiente de segregação do íon Nd3+ é próximo à unidade nesta matriz. O ganho potencial para ação laser foi determinado utilizando-se uma solução numérica das equações de taxa do sistema em 805nm e regime CW. O ganho máximo da emissão laser em 1,064 μm foi previsto para a dopagem de 5% mol Nd3+. / Tese (Doutoramento) / IPEN/T / Instituto de Pesquisas Energeticas e Nucleares - IPEN-CNEN/SP

Orientador: Roberto Jose Maria Covolan / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Fisica Gleb Wataghin / Made available in DSpace on 2018-08-12T12:47:40Z (GMT). No. of bitstreams: 1 Mesquita_RicksonCoelho_D.pdf: 22300712 bytes, checksum: 11bd3fc16a125afc1c2cd8b4d18bc2e2 (MD5) Previous issue date: 2009 / Resumo: A atividade neuronal relacionada a um determinado estímulo ou tarefa induz uma cadeia de complexos eventos biológicos no cérebro. O aumento no consumo de energia induz um acréscimo na demanda por glicose e oxigênio no tecido extravascular. Fatores bioquímicos e neuronais induzem variações nos vasos sanguíneos que resultam em alterações de uxo sanguíneo, volume e oxigenação. Embora extensivamente investigada, esta cascata de eventos ainda é pouco compreendida. Neste projeto, procuramos descrever o acoplamento entre os níveis celular, metabólico e vascular associado à ativação funcional do cérebro. Usando medidas eletro fisiológicas, modelamos os sistemas neuro-vascular e neuro-metabólico para descrever a hemodinâmica cerebral medida através de técnicas ópticas. Resultados obtidos em ratos durante a estimulação de um fio de bigode mostraram que a determinação de uma função resposta para cada sistema, assumido como linear, descreve bem o comportamento hemodinâmico e possibilita o estudo dos estados vascular e metabólico caracterizados pelos parâmetros medidos. A partir de experimentos multimodais de NIRS e fMRI, desenvolvemos metodologias inovadoras para a determinação de imagens metabólicas, capazes de prever variações do consumo de oxigênio com boa resolução espacial e temporal. Por fim, analisamos a in u^encia de parâmetros fisiológicos no sinal óptico, mostrando a contribuição importante da pressão sanguínea na composição deste. Medidas de correlação temporal foram projetadas para gerar mapas de correlação vascular que podem ser aplicados ao estudo da conectividade vascular cerebral, tanto em indivíduos normais como em pacientes com patologias cerebrais. / Abstract: Task-associated neuronal activity leads to a complex chain of biological events within the brain. The increased energetics gives rise to elevated glucose and oxygen consumption in the tissue. Biochemical and neuronal factors induce changes in blood vessels and variations in blood ow, volume and oxygenation. Although it has been extensively investigated, this cascade of events is still poorly understood and highly debated. In this project, the aim was to describe the coupling among the cellular, metabolic and vascular levels associated to functional brain activation. Using electrophysiological measurements, we modeled the neuro-vascular and neuro-metabolic systems in order to describe cerebral hemodynamics as seen through optical techniques. Results obtained in rats during whisker-barrel stimulation showed that the determination of a response function for each system, assumed as linear, can describe the hemodynamic behavior and allow the study of the vascular and metabolic states characterized by the measurements. From multimodal experiments of NIRS and fMRI, we developed unique methods to the determination of metabolic images, which can predict changes in oxygen consumption with good temporal and spatial resolution. Finally, we analyzed the in uence of the physiology in the optical signal, and showed the importance of taking into account blood pressure oscillations into this signal. Measurements of temporal correlation were projected to generate vascular correlation maps that may be useful to the study of cerebral vascular connectivity, both in normal subjects and in patients with cerebral pathologies. / Doutorado / Metodos Oticos de Analise / Doutor em Ciências

L’approximation par harmoniques sphériques (SPN) simplifiées de l’équation de transfert radiatif a été proposée comme un modèle fiable de propagation de la lumière dans les tissus biologiques. Cependant, peu de solutions analytiques ont été trouvées pour ce modèle. De telles solutions analytiques sont d’une grande valeur pour valider les solutions numériques des équations SPN, auxquelles il faut recourir dans le cas de tissus avec des géométries courbes complexes. Dans la première partie de cette thèse, des solutions analytiques pour deux géométries courbes sont présentées pour la première fois, à savoir pour la sphère et pour le cylindre. Pour les deux solutions, les conditions aux frontières générales tenant compte du saut d’indice de réfraction à l’interface du tissus et de son milieu environnant, telles qu’applicables à l’optique biomédicale, sont utilisées. Ces solutions sont validées à l’aide de simulations Monte Carlo basées sur un maillage de discrétisation du milieu. Ainsi, ces solutions permettent de valider rapidement un code numérique, par exemple utilisant les différences finies ou les éléments finis, sans nécessiter de longues simulations Monte Carlo. Dans la deuxième partie de cette thèse, la reconstruction itérative pour l’imagerie par tomographie optique diffuse par fluorescence est proposée sur la base d’une fonction objective et de son terme de régularisation de type Lq-Lp. Pour résoudre le problème inverse d’imagerie, la discrétisation du modèle de propagation de la lumière est effectuée en utilisant la méthode des différences finies. La reconstruction est effectuée sur un modèle de souris numérique en utilisant un maillage multi-échelle. Le problème inverse est résolu itérativement en utilisant une méthode d’optimisation. Pour cela, le gradient de la fonction de coût par rapport à la carte de concentration de l’agent fluorescent est nécessaire. Ce gradient est calculé à l’aide d’une méthode adjointe. Des mesures quantitatives utilisées en l’imagerie médicale sont utilisées pour évaluer la performance de l’approche de reconstruction dans différentes conditions. L’approche Lq-Lp montre des performances quantifiées élevées par rapport aux algorithmes traditionnels basés sur des fonction coût de type somme de carrés de différences. / Abstract : The simplified spherical harmonics (SPN) approximation to the radiative transfer equation has been proposed as a reliable model of light propagation in biological tissues. However, few analytical solutions have been found for this model. Such analytical solutions are of great value to validate numerical solutions of the SPN equations, which must be resorted to when dealing with media with complex curved geometries. In the first part of this thesis, analytical solutions for two curved geometries are presented for the first time, namely for the sphere and for the cylinder. For both solutions, the general refractiveindex mismatch boundary conditions, as applicable in biomedical optics, are resorted to. These solutions are validated using mesh-based Monte Carlo simulations. So validated, these solutions allow in turn to rapidly validate numerical code, based for example on finite differences or on finite elements, without requiring lengthy Monte Carlo simulations. provide reliable tool for validating numerical simulations. In the second part, iterative reconstruction for fluorescence diffuse optical tomography imaging is proposed based on an Lq-Lp framework for formulating an objective function and its regularization term. To solve the imaging inverse problem, the discretization of the light propagation model is performed using the finite difference method. The framework is used along with a multigrid mesh on a digital mouse model. The inverse problem is solved iteratively using an optimization method. For this, the gradient of the cost function with respect to the fluorescent agent’s concentration map is necessary. This is calculated using an adjoint method. Quantitative metrics resorted to in medical imaging are used to evaluate the performance of the framework under different conditions. The results obtained support this new approach based on an Lq-Lp formulation of cost functions in order to solve the inverse fluorescence problem with high quantified performance.

Since the inverse problem in Diffusive Optical Tomography (DOT) is nonlinear and severely ill-posed, only low resolution reconstructions are feasible when noise is added to the data nowadays. The purpose of this thesis is to improve image reconstruction in DOT of the main optical properties of tissues with some novel mathematical methods. We have used the Landweber (L) method, the Landweber-Kaczmarz (LK) method and its improved Loping-Landweber-Kaczmarz (L-LK) method combined with sparsity or with total variation regularizations for single and simultaneous image reconstructions of the absorption and scattering coefficients. The sparsity method assumes the existence of a sparse solution which has a simple description and is superposed onto a known background. The sparsity method is solved using a smooth gradient and a soft thresholding operator. Moreover, we have proposed an improved sparsity method. For the total variation reconstruction imaging, we have used the split Bregman method and the lagged diffusivity method. For the total variation method, we also have implemented a memory-efficient method to minimise the storage of large Hessian matrices. In addition, an individual and simultaneous contrast value reconstructions are presented using the level set (LS) method. Besides, the shape derivative of DOT based on the RTE is derived using shape sensitivity analysis, and some reconstructions for the absorption coefficient are presented using this shape derivative via the LS method.\\Whereas most of the approaches for solving the nonlinear problem of DOT make use of the diffusion approximation (DA) to the radiative transfer equation (RTE) to model the propagation of the light in tissue, the accuracy of the DA is not satisfactory in situations where the medium is not scattering dominant, in particular close to the light sources and to the boundary, as well as inside low-scattering or non-scattering regions. Therefore, we have solved the inverse problem in DOT by the more accurate time-dependant RTE in two dimensions.

The main theme of this work is effectiveness and efficiency of Krylov subspace methods and Krylov subspace recycling. While solving long, slowly changing sequences of large linear systems, such as the ones that arise in engineering, there are many issues we need to consider if we want to make the process reliable (converging to a correct solution) and as fast as possible. This thesis is built on three main components. At first, we target bilinear and quadratic form estimation. Bilinear form $c^TA^{-1}b$ is often associated with long sequences of linear systems, especially in optimization problems. Thus, we devise algorithms that adapt cheap bilinear and quadratic form estimates for Krylov subspace recycling. In the second part, we develop a hybrid recycling method that is inspired by a complex CFD application. We aim to make the method robust and cheap at the same time. In the third part of the thesis, we optimize the implementation of Krylov subspace methods on Graphic Processing Units (GPUs). Since preconditioners based on incomplete matrix factorization (ILU, Cholesky) are very slow on the GPUs, we develop a preconditioner that is effective but well suited for GPU implementation. / Ph. D. / In many applications we encounter the repeated solution of a large number of slowly changing large linear systems. The cost of solving these systems typically dominates the computation. This is often the case in medical imaging, or more generally inverse problems, and optimization of designs. Because of the size of the matrices, Gaussian elimination is infeasible. Instead, we find a sufficiently accurate solution using iterative methods, so-called Krylov subspace methods, that improve the solution with every iteration computing a sequence of approximations spanning a Krylov subspace. However, these methods often take many iterations to construct a good solution, and these iterations can be expensive. Hence, we consider methods to reduce the number of iterations while keeping the iterations cheap. One such approach is Krylov subspace recycling, in which we recycle judiciously selected subspaces from previous linear solves to improve the rate of convergence and get a good initial guess. In this thesis, we focus on improving efficiency (runtimes) and effectiveness (number of iterations) of Krylov subspace methods. The thesis has three parts. In the first part, we focus on efficiently estimating sequences of bilinear forms, c^TA⁻¹b. We approximate the bilinear forms using the properties of Krylov subspaces and Krylov subspace solvers. We devise an algorithm that allows us to use Krylov subspace recycling methods to efficiently estimate bilinear forms, and we test our approach on three applications: topology optimization for the optimal design of structures, diffuse optical tomography, and error estimation and grid adaptation in computational fluid dynamics. In the second part, we focus on finding the best strategy for Krylov subspace recycling for two large computational fluid dynamics problems. We also present a new approach, which lets us reduce the computational cost of Krylov subspace recycling. In the third part, we investigate Krylov subspace methods on Graphics Processing Units. We use a lid driven cavity problem from computational fluid dynamics to perform a thorough analysis of how the choice of the Krylov subspace solver and preconditioner influences runtimes. We propose a new preconditioner, which is designed to work well on Graphics Processing Units.

Ce travail de thèse concerne le traitement d’image fDOT (fDOT pour fluorescence diffuse optical tomography) suit vers deux axes. Le recalage d'images fDOT à l’aide de l’imagerie TEP (tomographie par émission de positons) et l’amélioration des reconstructions fDOT à l’aide de miroirs pour collecter des projections complémentaires. Il est présenté en deux parties : Dans la première partie, une méthode automatique pour recaler les images de fDOT avec les images de Tomographie par Emission de Positons (TEP) développée dans le but de corréler l’ensemble des informations issues de chaque modalité. Cette méthode de recalage est basée sur une détection automatique de marqueurs fiduciaires présents dans les deux modalités. La particularité de cette méthode est l’utilisation de l’image de surface obtenue en fDOT, qui sert à identifier la position en Z des marqueurs fiduciaires dans les images optiques. Nous avons testé cette méthode sur un modèle de souris porteuses de xénogreffes de tumeurs de cellules cancéreuses MEN2A qui imitent un carcinome thyroïdien médullaire humain, après une double injection de traceur radioactif : [18F]2-fluoro-2-Deoxy-D-glucose (FDG) pour l’imagerie TEP et un traceur optique d’infrarouge fluorescent, le Sentidye. Grâce à la précision de notre méthode, nous arrivons à démontrer que le signal Sentidye est présent à la fois dans la tumeur et les vaisseaux environnants [1]. La qualité des images fDOT est dégradée selon l’axe Z du fait d’un nombre limité de projections pour la reconstruction. Dans la deuxième partie, le travail s’est orienté vers une nouvelle méthode de reconstruction d’images fDOT à partir d’un nouveau système d’acquisition multi-angulaire avec deux miroirs placés de chaque côté de l’animal. Ce travail a été mené en collaboration avec le département CS d’University College London (UCL), partenaire du projet Européen FMT-XCT. Le logiciel TOAST développé par cette équipe a été utilisé comme source pour l’algorithme de reconstruction, et modifié pour s’adapter à notre problématique. Après plusieurs essais concernant l’ajustement des paramètres du programme, nous avons appliqué cette méthode sur un fantôme réaliste des tissus biologiques et chez la souris. Les résultats montrent une amélioration de l’image reconstruite d’un fantôme semi-cylindrique et de l’image de rein chez la souris, pour lesquelles la méthode des miroirs est supérieure à la méthode classique sans miroir. Malgré tout, nous avons observé que les résultats étaient très sensibles à certains paramètres, d’où une performance de reconstruction variable d’un cas à l’autre. Les perspectives futures concernent l’optimisation des paramètres afin de généraliser l’approche multi-angle. / This thesis concerns the image processing of fluorescence diffuse optical tomography (fDOT), following two axes: FDOT image co-registration with PET (positron emission tomography) image and improvement of fDOT image reconstructions using mirrors to collect additional projections. It is presented in two parts:In the first part, an automatic method to co-register the fDOT images with PET images has been developed to correlate all the information from each modality. This co-registration method is based on automatic detection of fiducial markers (FM) present in both modalities. The particularity of this method is the use of optical surface image obtained in fDOT imaging system, which serves to identify the Z position of FM in optical images. We tested this method on a model of mice bearing tumor xenografts of MEN2A cancer cells that mimic a human medullary thyroid carcinoma, after a double injection of radiotracer [18F] 2-fluoro-2-Deoxy-D-glucose ( FDG) for PET imaging and optical fluorescent infrared tracer Sentidye. With the accuracy of our method, we can demonstrate that the signal of Sentidye is present both in the tumor and surrounding vessels.The fDOT reconstruction image quality is degraded along the Z axis due to a limited number of projections for reconstruction. In the second part, the work is oriented towards a new method of fDOT image reconstruction with a new multi-angle data acquisition system in placing two mirrors on each side of the animal. This work was conducted in collaboration with the CS Department of University College London (UCL), a partner of the European project FMT-XCT. TOAST software developed by this team was used as source code for the reconstruction algorithm, and was modified to adapt to the concerned problem. After several tests on the adjustment of program parameters, we applied this method on a phantom that simulating the biological tissue and on mice. The results showed an improvement in the reconstructed image of a semi-cylindrical phantom and the image of mouse kidney, for which the reconstruction of the mirrors geometry is better than that of conventional geometry without mirror. Nevertheless, we observed that the results were very sensitive to certain parameters, where the performance of reconstruction varies from one case to another. Future prospectives concern the optimization of parameters in order to generalize the multi-angle approach.

This thesis reports the work done towards design and fabrication of a versatile and low cost, frequency domain DOT (Diffuse Optical Tomography) Imager. A design which uses only a single fiber for the source and a single fiber bundle for the detector is reported. From near the source, to diametrically opposite to the source, the detected intensity of scattered light varies by three to four orders in magnitude, depending on the tissue/phantom absorption and scattering properties. The photo multiplier tube’s (PMT’s) gain is controlled to operate it in the linear range, thus increasing the dynamic range of detection. Increasing the dynamic range by multi channel data acquisition is also presented. Arresting the oscillations of a stepper using a negative torque braking method is also adopted in this application for increasing the speed of data acquisition. The finite element method (FEM) for obtaining photon density solution to the transport equation and the model based iterative image reconstruction (MPBIIR) algorithm are developed for verifying the experimental prototype. Simulation studies presented towards the end of this thesis work provide insight into the nature of measurements. The optical absorption reconstructed images from the simulation, verified the validity of implementation of the reconstruction method for further reconstructions from data gathered from the developed imager. A single iteration of MOBIIR to segment the region of interest (ROI) using an homogeneous measurement estimate is presented. Using the single iteration MOBIIR to obtain a relatively more accurate starting value for the optical absorption coefficient, and the reconstruction results for data obtained from tissue mimicking solid epoxy-resin phantom with a single in-homogeneity inclusion is also presented to demonstrate the imager prototype.

Am 14. Oktober 1999 wurde in Rossendorf die dritte Veranstaltung in einer Serie von Workshops über Meßtechnik für stationäre und transiente Mehrphasenströmungen durchgeführt. Dieses Jahr kann auf auf 11 interessante Vorträge zurückgeblickt werden. Besonders hervorzuheben sind die beiden Hauptvorträge, die von Herrn Professor Hetsroni aus Haifa und Herrn Dr. Sengpiel aus Karlsruhe gehalten wurden. Erneut lag ein wichtiger Schwerpunkt auf Meßverfahren, die räumliche Verteilungen von Phasenanteilen und Geschwindigkeiten sowie die Größe von Partikeln bzw. Blasen der dispersen Phase zugänglich machen. So wurde über einen dreidimensional arbeitenden Röntgentomographen, ein Verfahren zur Messung von Geschwindigkeitsprofilen mit Gittersensoren und eine Methode zur simultanen Messung von Blasengrößen sowie Feldern von Gas- und Flüssigkeitsgeschwindigkeit mit einer optischen Partikelverfolgungstechnik vorgetragen. Daneben wurden interessante Entwicklungen auf dem Gebiet der lokalen Sonden vorgestellt, wie z.B. eine Elektrodiffusionssonde. Neue meßtechnische Ansätze waren ebenfalls vertreten; hervorzuheben ist der Versuch, die Methode der optischen Tomographie für die Untersuchung von Zweiphasenströmungen nutzbar zu machen. Der Tagungsband enthält die folgenden Beiträge: S. John, R. Wilfer, N. Räbiger, Universität Bremen, Messung hydrodynamischer Parameter in Mehrphasenströmungen bei hohen Dispersphasengehalten mit Hilfe der Elektrodiffusionsmeßtechnik E. Krepper, A. Aszodi, Forschungszentrum Rossendorf, Temperatur- und Dampfgehaltsverteilungen bei Sieden in seitlich beheizten Tanks D. Hoppe, Forschungszentrum Rossendorf, Ein akustisches Resonanzverfahren zur Klassifizierung von Füllständen W. Sengpiel, V. Heinzel, M. Simon, Forschungszentrum Karlsruhe, Messungen der Eigenschaften von kontinuierlicher und disperser Phase in Luft-Wasser-Blasenströmungen R. Eschrich, VDI, Die Probestromentnahme zur Bestimmung der dispersen Phase einer Zweiphasenströmung U. Hampel, TU Dresden, Optische Tomographie O. Borchers, C. Busch, G. Eigenberger, Universität Stuttgart, Analyse der Hydrodynamik in Blasenströmungen mit einer Bildverarbeitungsmethode C. Zippe, Forschungszentrum Rossendorf, Beobachtung der Wechselwirkung von Blasen mit Gittersensoren mit einer Hochgeschwindigkeits-Videokamera H.-M. Prasser, Forschungszentrum Rossendorf, Geschwindigkeits- und Durchflußmessung mit Gittersensoren

Computational imaging has been playing an important role in understanding and analysing the captured images. Both image segmentation and restoration has been in-tegral parts of computational imaging. The studies performed in this thesis has been focussed toward developing novel algorithms for image segmentation and restoration. Study related to usage of Morozov Discrepancy Principle in Di use Optical Imaging was also presented here to show that hyper parameter selection could be performed with ease. The Laplacian of Gaussian (LoG) and Canny operators use Gaussian smoothing be-fore applying the derivative operator for edge detection in real images. The LoG kernel was based on second derivative and is highly sensitive to noise when compared to the Canny edge detector. A new edge detection kernel, called as Helmholtz of Gaussian (HoG), which provides higher di suavity is developed in this thesis and it was shown that it is more robust to noise. The formulation of the developed HoG kernel is similar to LoG. It was also shown both theoretically and experimentally that LoG is a special case of HoG. This kernel when used as an edge detector exhibited superior performance compared to LoG, Canny and wavelet based edge detector for the standard test cases both in one- and two-dimensions. The linear inverse problem encountered in restoration of blurred noisy images is typically solved via Tikhonov minimization. The outcome (restored image) of such min-imitation is highly dependent on the choice of regularization parameter. In the absence of prior information about the noise levels in the blurred image, ending this regular-inaction/hyper parameter in an automated way becomes extremely challenging. The available methods like Generalized Cross Validation (GCV) may not yield optimal re-salts in all cases. A novel method that relies on minimal residual method for ending the regularization parameter automatically was proposed here and was systematically compared with the GCV method. It was shown that the proposed method performance was superior to the GCV method in providing high quality restored images in cases where the noise levels are high Di use optical tomography uses near infrared (NIR) light as the probing media to recover the distributions of tissue optical properties with an ability to provide functional information of the tissue under investigation. As NIR light propagation in the tissue is dominated by scattering, the image reconstruction problem (inverse problem) is non-linear and ill-posed, requiring usage of advanced computational methods to compensate this. An automated method for selection of regularization/hyper parameter that incorporates Morozov discrepancy principle(MDP) into the Tikhonov method was proposed and shown to be a promising method for the dynamic Di use Optical Tomography.