983 resultados para diffusion MRI


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Le dioxyde de carbone (CO2) est un résidu naturel du métabolisme cellulaire, la troisième substance la plus abondante du sang, et un important agent vasoactif. À la moindre variation de la teneur en CO2 du sang, la résistance du système vasculaire cérébral et la perfusion tissulaire cérébrale subissent des changements globaux. Bien que les mécanismes exacts qui sous-tendent cet effet restent à être élucidés, le phénomène a été largement exploité dans les études de réactivité vasculaire cérébrale (RVC). Une voie prometteuse pour l’évaluation de la fonction vasculaire cérébrale est la cartographie de la RVC de manière non-invasive grâce à l’utilisation de l’Imagerie par Résonance Magnétique fonctionnelle (IRMf). Des mesures quantitatives et non-invasives de de la RVC peuvent être obtenus avec l’utilisation de différentes techniques telles que la manipu- lation du contenu artériel en CO2 (PaCO2) combinée à la technique de marquage de spin artériel (Arterial Spin Labeling, ASL), qui permet de mesurer les changements de la perfusion cérébrale provoqués par les stimuli vasculaires. Toutefois, les préoccupations liées à la sensibilité et la fiabilité des mesures de la RVC limitent de nos jours l’adoption plus large de ces méthodes modernes de IRMf. J’ai considéré qu’une analyse approfondie ainsi que l’amélioration des méthodes disponibles pourraient apporter une contribution précieuse dans le domaine du génie biomédical, de même qu’aider à faire progresser le développement de nouveaux outils d’imagerie de diagnostique. Dans cette thèse je présente une série d’études où j’examine l’impact des méthodes alternatives de stimulation/imagerie vasculaire sur les mesures de la RVC et les moyens d’améliorer la sensibilité et la fiabilité de telles méthodes. J’ai aussi inclus dans cette thèse un manuscrit théorique où j’examine la possible contribution d’un facteur méconnu dans le phénomène de la RVC : les variations de la pression osmotique du sang induites par les produits de la dissolution du CO2. Outre l’introduction générale (Chapitre 1) et les conclusions (Chapitre 6), cette thèse comporte 4 autres chapitres, au long des quels cinq différentes études sont présentées sous forme d’articles scientifiques qui ont été acceptés à des fins de publication dans différentes revues scientifiques. Chaque chapitre débute par sa propre introduction, qui consiste en une description plus détaillée du contexte motivant le(s) manuscrit(s) associé(s) et un bref résumé des résultats transmis. Un compte rendu détaillé des méthodes et des résultats peut être trouvé dans le(s) dit(s) manuscrit(s). Dans l’étude qui compose le Chapitre 2, je compare la sensibilité des deux techniques ASL de pointe et je démontre que la dernière implémentation de l’ASL continue, la pCASL, offre des mesures plus robustes de la RVC en comparaison à d’autres méthodes pulsés plus âgées. Dans le Chapitre 3, je compare les mesures de la RVC obtenues par pCASL avec l’utilisation de quatre méthodes respiratoires différentes pour manipuler le CO2 artérielle (PaCO2) et je démontre que les résultats peuvent varier de manière significative lorsque les manipulations ne sont pas conçues pour fonctionner dans l’intervalle linéaire de la courbe dose-réponse du CO2. Le Chapitre 4 comprend deux études complémentaires visant à déterminer le niveau de reproductibilité qui peut être obtenu en utilisant des méthodes plus récentes pour la mesure de la RVC. La première étude a abouti à la mise au point technique d’un appareil qui permet des manipulations respiratoires du CO2 de manière simple, sécuritaire et robuste. La méthode respiratoire améliorée a été utilisée dans la seconde étude – de neuro-imagerie – où la sensibilité et la reproductibilité de la RVC, mesurée par pCASL, ont été examinées. La technique d’imagerie pCASL a pu détecter des réponses de perfusion induites par la variation du CO2 dans environ 90% du cortex cérébral humain et la reproductibilité de ces mesures était comparable à celle d’autres mesures hémodynamiques déjà adoptées dans la pratique clinique. Enfin, dans le Chapitre 5, je présente un modèle mathématique qui décrit la RVC en termes de changements du PaCO2 liés à l’osmolarité du sang. Les réponses prédites par ce modèle correspondent étroitement aux changements hémodynamiques mesurés avec pCASL ; suggérant une contribution supplémentaire à la réactivité du système vasculaire cérébral en lien avec le CO2.

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Travail réalisé à l'EBSI, Université de Montréal, sous la direction de M. Yvon Lemay dans le cadre du cours SCI6850 – Recherche individuelle, à l'hiver 2015

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This paper presents a method based on articulated models for the registration of spine data extracted from multimodal medical images of patients with scoliosis. With the ultimate aim being the development of a complete geometrical model of the torso of a scoliotic patient, this work presents a method for the registration of vertebral column data using 3D magnetic resonance images (MRI) acquired in prone position and X-ray data acquired in standing position for five patients with scoliosis. The 3D shape of the vertebrae is estimated from both image modalities for each patient, and an articulated model is used in order to calculate intervertebral transformations required in order to align the vertebrae between both postures. Euclidean distances between anatomical landmarks are calculated in order to assess multimodal registration error. Results show a decrease in the Euclidean distance using the proposed method compared to rigid registration and more physically realistic vertebrae deformations compared to thin-plate-spline (TPS) registration thus improving alignment.

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On line isotope separation techniques (ISOL) for production of ion beams of short-lived radionuclides require fast separation of nuclear reaction products from irradiated target materials followed by a transfer into an ion source. As a first step in this transport chain the release of nuclear reaction products from refractory metals has been studied systematically and will be reviewed. High-energy protons (500 - 1000 MeV) produce a large number of radionuclides in irradiated materials via the nuclear reactions spallation, fission and fragmentation. Foils and powders of Re, W, Ta, Hf, Mo, Nb, Zr, Y, Ti and C were irradiated with protons (600 - 1000 MeV) at the Dubna synchrocyclotron, the CERN synchrocyclotron and at the CERN PS-booster to produce different nuclear reaction products. The main topic of the paper is the determination of diffusion coefficients of the nuclear reaction products in the target matrix, data evaluation and a systematic interpretation of the data. The influence of the ionic radius of the diffusing species and the lattice type of the host material used as matrix or target on the diffusion will be evaluated from these systematics. Special attention was directed to the release of group I, II and III-elements. Arrhenius plots lead to activation energies of the diffusion process.

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A simple method based on laser beam deflection to study the variation of diffusion coefficient with concentration in a solution is presented. When a properly fanned out laser beam is passed through a rectangular cell filled with solution having concentration gradient, the emergent beam traces out a curved pattern on a screen. By taking measurements on the pattern at different concentrations, the variation of diffusion coefficient with concentration can be determined.

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In the present study, radio frequency plasma polymerization technique is used to prepare thin films of polyaniline, polypyrrole, poly N-methyl pyrrole and polythiophene. The thermal characterization of these films is carried out using transverse probe beam deflection method. Electrical conductivity and band gaps are also determined. The effect of iodine doping on electrical conductivity and the rate of heat diffusion is explored.Bulk samples of poyaniline and polypyrrole in powder form are synthesized by chemical route. Open photoacoustic cell configuration is employed for the thermal characterization of these samples. The effect of acid doping on heat diffusion in these bulk samples of polyaniline is also investigated. The variation of electrical conductivity of doped polyaniline and polypyrrole with temperature is also studied for drawing conclusion on the nature of conduction in these samples. In order to improve the processability of polyaniline and polypyrrole, these polymers are incorporated into a host matrix of poly vinyl chloride. Measurements of thermal diffusivity and electrical conductivity of these samples are carried out to investigate the variation of these quantities as a function of the content of polyvinyl chloride.

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In a recent paper [Phys. Rev. B 50, 3477 (1994)], P. Fratzl and O. Penrose present the results of the Monte Carlo simulation of the spinodal decomposition problem (phase separation) using the vacancy dynamics mechanism. They observe that the t1/3 growth regime is reached faster than when using the standard Kawasaki dynamics. In this Comment we provide a simple explanation for the phenomenon based on the role of interface diffusion, which they claim is irrelevant for the observed behavior.

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A model has been developed for evaluating grain size distributions in primary crystallizations where the grain growth is diffusion controlled. The body of the model is grounded in a recently presented mean-field integration of the nucleation and growth kinetic equations, modified conveniently in order to take into account a radius-dependent growth rate, as occurs in diffusion-controlled growth. The classical diffusion theory is considered, and a modification of this is proposed to take into account interference of the diffusion profiles between neighbor grains. The potentiality of the mean-field model to give detailed information on the grain size distribution and transformed volume fraction for transformations driven by nucleation and either interface- or diffusion-controlled growth processes is demonstrated. The model is evaluated for the primary crystallization of an amorphous alloy, giving an excellent agreement with experimental data. Grain size distributions are computed, and their properties are discussed.

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The study of simple chaotic maps for non-equilibrium processes in statistical physics has been one of the central themes in the theory of chaotic dynamical systems. Recently, many works have been carried out on deterministic diffusion in spatially extended one-dimensional maps This can be related to real physical systems such as Josephson junctions in the presence of microwave radiation and parametrically driven oscillators. Transport due to chaos is an important problem in Hamiltonian dynamics also. A recent approach is to evaluate the exact diffusion coefficient in terms of the periodic orbits of the system in the form of cycle expansions. But the fact is that the chaotic motion in such spatially extended maps has two complementary aspects- - diffusion and interrnittency. These are related to the time evolution of the probability density function which is approximately Gaussian by central limit theorem. It is noticed that the characteristic function method introduced by Fujisaka and his co-workers is a very powerful tool for analysing both these aspects of chaotic motion. The theory based on characteristic function actually provides a thermodynamic formalism for chaotic systems It can be applied to other types of chaos-induced diffusion also, such as the one arising in statistics of trajectory separation. It was noted that there is a close connection between cycle expansion technique and characteristic function method. It was found that this connection can be exploited to enhance the applicability of the cycle expansion technique. In this way, we found that cycle expansion can be used to analyse the probability density function in chaotic maps. In our research studies we have successfully applied the characteristic function method and cycle expansion technique for analysing some chaotic maps. We introduced in this connection, two classes of chaotic maps with variable shape by generalizing two types of maps well known in literature.

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A spectral angle based feature extraction method, Spectral Clustering Independent Component Analysis (SC-ICA), is proposed in this work to improve the brain tissue classification from Magnetic Resonance Images (MRI). SC-ICA provides equal priority to global and local features; thereby it tries to resolve the inefficiency of conventional approaches in abnormal tissue extraction. First, input multispectral MRI is divided into different clusters by a spectral distance based clustering. Then, Independent Component Analysis (ICA) is applied on the clustered data, in conjunction with Support Vector Machines (SVM) for brain tissue analysis. Normal and abnormal datasets, consisting of real and synthetic T1-weighted, T2-weighted and proton density/fluid-attenuated inversion recovery images, were used to evaluate the performance of the new method. Comparative analysis with ICA based SVM and other conventional classifiers established the stability and efficiency of SC-ICA based classification, especially in reproduction of small abnormalities. Clinical abnormal case analysis demonstrated it through the highest Tanimoto Index/accuracy values, 0.75/98.8%, observed against ICA based SVM results, 0.17/96.1%, for reproduced lesions. Experimental results recommend the proposed method as a promising approach in clinical and pathological studies of brain diseases

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In this paper, we propose a multispectral analysis system using wavelet based Principal Component Analysis (PCA), to improve the brain tissue classification from MRI images. Global transforms like PCA often neglects significant small abnormality details, while dealing with a massive amount of multispectral data. In order to resolve this issue, input dataset is expanded by detail coefficients from multisignal wavelet analysis. Then, PCA is applied on the new dataset to perform feature analysis. Finally, an unsupervised classification with Fuzzy C-Means clustering algorithm is used to measure the improvement in reproducibility and accuracy of the results. A detailed comparative analysis of classified tissues with those from conventional PCA is also carried out. Proposed method yielded good improvement in classification of small abnormalities with high sensitivity/accuracy values, 98.9/98.3, for clinical analysis. Experimental results from synthetic and clinical data recommend the new method as a promising approach in brain tissue analysis.

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This work presents an efficient method for volume rendering of glioma tumors from segmented 2D MRI Datasets with user interactive control, by replacing manual segmentation required in the state of art methods. The most common primary brain tumors are gliomas, evolving from the cerebral supportive cells. For clinical follow-up, the evaluation of the pre- operative tumor volume is essential. Tumor portions were automatically segmented from 2D MR images using morphological filtering techniques. These seg- mented tumor slices were propagated and modeled with the software package. The 3D modeled tumor consists of gray level values of the original image with exact tumor boundary. Axial slices of FLAIR and T2 weighted images were used for extracting tumors. Volumetric assessment of tumor volume with manual segmentation of its outlines is a time-consuming proc- ess and is prone to error. These defects are overcome in this method. Authors verified the performance of our method on several sets of MRI scans. The 3D modeling was also done using segmented 2D slices with the help of a medical software package called 3D DOCTOR for verification purposes. The results were validated with the ground truth models by the Radi- ologist.

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En aquest article es resumeixen els resultats publicats en un informe de l' ISS (Istituto Superiore di Sanità) del desembre de 2006, sobre un model matemàtic desenvolupat per un grup de treball que inclou a investigadors de les Universitats de Trento, Pisa i Roma, i els Instituts Nacionals de Salut (Istituto Superiore di Sanità, ISS), per avaluar i mesurar l'impacte de la transmissió i el control de la pandèmia de grip

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Actualment, en l'àmbit mèdic, la ressonància magnètica, MRI Magnetic Resonance Imaging, és un dels sistemes més utilitzats per a la realització de diagnòstics i el seguiment de l'evolució de malalties com l'esclerosi múltiple (EM). No obstant, la gran quantitat d'informació que proporciona aquesta modalitat té com a conseqüència una tasca feixuga d'anàlisi i d'interpretació per part dels radiòlegs i neuròlegs. L'objectiu general d'aquest projecte és desenvolupar un sistema per ajudar als metges a segmentar les imatges de MRI del cervell. S'ha implementat amb MATLAB. Durant tot el procés s'han utilitzat dades sintètiques, de la base de dades simulada BrainWeb, i reals, proporcionades pels grup de metges col•laboradors amb el grup VICOROB. El projecte s'emmarca dins d'un projecte de recerca del grup de Visió per Computador i Robòtica de la Universitat de Girona

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Comparar el resultado de la resonancia magnética en el diagnóstico de apendicitis aguda con el patrón de oro (estudio histopatológico o seguimiento clínico del paciente) con el fin de establecer la utilidad de ésta como prueba diagnóstica y poder incluirla dentro del algoritmo de estudio de esta patología cuando hay sospecha clínica y un resultado negativo o dudoso de la ecografía abdominal