O Dilema do Prisioneiro (DP) é o jogo mais proeminente da Teoria dos Jogos devido à emergência da cooperação entre jogadores egoístas. O comportamento de cada jogador depende da estratégia que ele adotada e do seu ganho, que é determinado em função dos parâmetros do DP (T, R, P e S) e do número z de vizinhos com que ele joga. Portanto, a estrutura espacial dos jogadores não é relevante. Em nosso trabalho, utilizamos um autômato celular unidimensional onde cada jogador pode cooperar ou desertar ao interagir, simetricamente, com seus z vizinhos mais próximos. O sistema proposto nos permitiu realizar um estudo exaustivo do espaço de parâmetros para as estratégias evolucionárias Darwiniana (EED) e a Pavloviana (EEP) e compara-las. A geometria unidimensional nos possibilita obter os mesmos resultados dos sistemas em dimensionalidade arbitrária d, além de apresentar várias vantagens em relação a elas. No sistema que propomos os efeitos de borda são menores, exige menos tempo para a execução das simulações numéricas, permite variar o valor de z e é fácil obter uma representação visual da evolução temporal do sistema. Tal visualização simplifica a compreensão das interações entre os jogadores, pois surgem padrões nos agrupamentos de cooperadores/desertores, semelhantes aos pertencentes às classes dos autômatos celulares elementares. O estudo destes padrões nos permite compreender simplesmente a emergência da cooperação ou deserção nos sistemas. A evolução temporal do sistema que adota a EED gera um diagrama de fases muito rico com a presença das fases cooperadora, desertora e caótica. Já para a EEP, obtivemos um novo resultado analítico para as transições de fase, que neste caso são: cooperadora e quasi-regular. O estudo numérico exaustivo determinou as regiões do espaço de parâmetros onde acontecem cada uma das fases, e os efeitos da auto-interação podendo assim validar os resultados teóricos. O estudo do caso particular T = 1, tradicionalmente considerado como trivial, mostrou que ele apresenta comportamentos inusitados. Nossa principal contribuição para o estudo do DP é a obtenção de um novo paradigma. A geometria unidimensional com interação de vizinhos simétricos permitiu a visualização da evolução de padrões de cooperadores e desertores, o cálculo analítico de Tc para a EEP e o estudo de T = 1 para tais sistemas. / The Prisoner Dilemma (PD) is the most prominent game of the Game Theory due to emergency of the cooperation between selfish players. The behavior of each player depends on his/her strategy and the payoff, which is determined in function of the PD parameters (T, R, P and S) and by the number z of neighbors with whom he/she plays. Therefore, the spatial structure of the players does not matter. In our work, we have used a one-dimensional cellular automaton where each player can cooperate or defect when interacting, symmetrically, with his/her z nearest neighbors. The considered system allowed us to carry out an exhaustive exploration of the parameters space for the Darwinian Evolutionary Strategy (EED) and Pavlovian (EEP) and compares them. One-dimensional geometry makes possible to us get the same results of the systems in arbitrary d dimensional networks, besides, it presents some advantages. For the system that we proposed compared to the others dimensional networks, the boundary effects are less present, it needs less time for run the numerical simulations, it allows to vary the z value and is easier to get the visual representation of the system temporal evolution. Such visualization simplifies the understanding of the interactions between the players, therefore patterns appear in the clusters of cooperator/defectors, and these patterns belong to the elementary cellular automata classes. The study of these patterns allows them to understand in an easy way the emergence of the cooperation or defection in the systems. The temporal evolution of the system that adopts the EED yields a very rich phases diagram with the presence of cooperative, defective and chaotic phases. By the other hand, for the EEP, we have got a new analytical result for the phase transitions that in this case are: quasi-regular and cooperative. The exhaustive exploration study determines the regions on the parameters space where happen each phases occurs, and the effect of the self-interaction and thus validate the theoretical results. The study of the particular case T = 1, traditionally considered as trivial one, showed that it presents unusual behaviors, that we will present. Our main contribution for the study of the DP is the attainment of a new paradigm. One-dimensional geometry with interaction of symmetrical neighbors allowed to visualizes the evolution of cooperators and defectors patterns, the analytical result for Tc for the EEP and the study of T = 1 for such systems.

Over the last decade advances in multineuron simultaneous recording techniques have produced huge amounts of data. This has led to the investigation of probable temporal relationships between spike times of neurons as manifestations of the underlying network structure. But the huge dimensionality of data makes the search for patterns difficult. Although this difficulty may be surpassed by employing massive computing resources, understanding the significance and relation of these temporal patterns to the underlying network structure and the causative activity is still difficult. To find such relationships in networks of excitatory neurons, a simplified network structure of feedforward chains called "Synfire chains" has been frequently employed. But in a recurrently connected network where activity from feedback connections is comparable to the feedforward chain, the basic assumptions underlying synfire chains are violated. In the first part of this thesis we propose the first-spike-latency based analysis as a low complexity method of studying the temporal relationships between neurons. Firstly, spike latencies being temporal delays measured at a particular epoch of time (onset of activity after a quiescent period) are a small subset of all the temporal information available in spike trains, thereby hugely reducing the amount of data that needs to be analyzed. We also define for the first time, "Synconset waves and chains" as a sequence of first-spike-times and the causative neuron chain. Using simulations, we show the efficacy of the synconset paradigm in unraveling feedforward chains of excitatory neurons even in a recurrent network. We further create a framework for going back and forth between network structure and the observed first-spike-latency patterns. To quantify these associations between network structure and dynamics we propose a likelihood measure based on Bayesian reasoning. This quantification is agnostic to the methods of association used and as such can be used with any of the existing approaches. We also show the benefits of such an analysis when the recorded data is subsampled, as is the case with most physiological recordings. In the subsequent part of our thesis we show two sample applications of first-spike-latency analysis on data acquired from multielectrode arrays. Our first application dwells on the intricacies of extracting first-spike-latency patterns from multineuron recordings using recordings of glutamate injured cultures. We study the significance of these patterns extracted vis-a-vis patterns that may be obtained from exponential spike latency distributions and show the differences between patterns obtained in injured and control cultures. In a subsequent application, we study the evolution of latency patterns over several days during the lifetime of a dissociated hippocampal culture.

A l’image du bassin du Congo, la République Démocratique du Congo (République Démocratique du Congo) fait face à une réduction de la qualité et de la superficie de son couvert forestier. La présente étude avait pour objectif d’étudier l’effet de l’anthropisation, à travers la présence et les activités humaines sur la dynamique des paysages forestiers en République Démocratique du Congo. L’écologie du paysage, en tant que science pluridisciplinaire offre une très bonne approche à travers les indices et une méthodologie alliant la structure et la composition du paysage pour mettre en évidence les causes et les conséquences des processus écologiques. Ces approches sont basées sur le fait que en analysant la structure du paysage, des déductions utiles au sujet des processus écologiques fondamentaux peuvent être faites et vice versa. Les résultats ont montré, en quantifiant la dynamique spatio-temporelle de l’occupation du sol et par l’analyse et la caractérisation de la structure spatiale, que l’anthropisation est le moteur de la dynamique dans ces milieux forestiers. L’impact humain se traduit par une déstabilisation ou un dysfonctionnement des écosystèmes forestiers entraînant la dégradation, la fragmentation et la déforestation. Ainsi il a été montré que la proximité des villes est fortement corrélée à la dégradation et la perte d’habitats forestiers. Cela est fonction de l’importance socio-économique de ces villes car plus la ville est importante, plus elle attire la population ;que la densité de la population influence la fragmentation et l’incursion dans la forêt se fait en suivant les pistes et les routes mises en place généralement par les sociétés d’exploitation forestière. Le tout amplifié par la situation socio-économique difficile des populations et le manque de politiques de gestion appropriées de la part des gestionnaires publiques. Cette dynamique régressive du paysage forestier en République Démocratique du Congo aura une incidence négative sur les cycles climatiques globaux vu que le bassin du Congo est le plus grand bloc forestier après le bloc de l’Amazonie. La présente étude est donc un argument supplémentaire qui milite en faveur de la nécessité de prendre en compte les caractéristiques des populations locales dans les programmes de gestion de la forêt du bassin du Congo pour un meilleur équilibre écologique de la planète. / Like Congo basin, Democratic Republic of Congo’s forest covers are facing their reduction in quality and size. This study aimed to investigate the effect of human impact on forest landscape dynamics in DR Congo, through the human presence and its activities. Landscape ecology as a multidisciplinary science offers a very good approach through the index and a methodology combining the structure and the composition of the landscape to highlight the causes and the consequences of ecological processes. These approaches are based on the fact that by analyzing the structure of landscape, useful deductions about the underlying ecological processes can be made and vice versa. By quantifying the spatio-temporal dynamics of land use and by analysis and characterization of spatial structure, our results showed that anthropization is the driver of the dynamics in these forest environments. Human impact results in a destabilization or a dysfunction of the forest ecosystems involving degradation, fragmentation and deforestation. Thus it was shown that proximity to cities is strongly correlated to the degradation and loss of forest habitats. This depends on the socioeconomic importance of these cities because more the city is important, more it attracts people. Population density influences the fragmentation and the incursion into the forest is done by following the tracks and roads generally implemented by the logging companies. All amplified by socio-economic problems of population and lack of appropriate management policies on the part of public managers.This regressive dynamic forest landscape in République Démocratique du Congo will have a negative impact on global climate cycles because the Congo Basin is the largest forest block after Amazonia block. This study is another argument which advocates the need to take into account the characteristics of local population in forest management programs in the Congo Basin for a better ecological balance of planet. / Doctorat en Sciences / info:eu-repo/semantics/nonPublished

Dans ce travail nous avons résolu deux problèmes principaux de la mise en forme topologique de faisceau paraxial pour les composants plans : la modalité et le polychromatisme.Nous les résolvons en introduisant de nouveaux concepts d’éléments optiques à interaction spin orbite,à savoir la “q-plate modale” et la “q-plate Bragg-Berry”. D’un côté, la q-plate modale convertit un faisceau gaussien incident en un faisceau de Laguerre-Gauss pour un indice radial et un indice d’azimut donnés, ce qui par conséquent dépasse les capacités des q-plates conventionnelles qui ne modifient que le degré de liberté azimutal, c.à.d. le moment orbital angulaire de la lumière. À des fins expérimentales, deux approches ont été développées : une basée sur des lames de verres nanostructurées artificiellement, l’autre sur des défauts topologiques de cristaux liquides auto-organisés naturellement. D’un autre côté, la q-plate Bragg-Berry consiste en une fine couche inhomogène de cristaux liquides chiraux (cholestériques) devant un miroir, ce qui fournit une mise en forme de faisceau spin-orbite pleinement efficace sur une large bande spectrale du faisceau incident, contrairement au q-plates conventionnelles qui ne sont fabriqués que pour une longueur d’onde donnée. Par ailleurs, nous obtenons une mise en forme de faisceau spin-orbite ultra-large bande en induisant une modulation de la structure supramoléculaire torsadée des cristaux liquides cholestériques selon la direction de propagation de la lumière. Nous montrons également que la présence du miroir derrière permet un puissant contrôle spatio-temporel des propriétés vectorielles de la polarisation du champ lumineux générées par la q-plate Bragg-Berry. / It is well-known that paraxial coherent electromagnetic fields can be completelycharacterized in terms of their radial and azimuthal spatial degrees of freedom in the transverse planethat add to the polarization degree of freedom and wavelength. In this work we address two mainissues of paraxial beam shaping that are the modality and the polychromaticity in the context of flatopticsthat we address by introducing novel concepts of spin-orbit optical elements. Namely, the‘modal q-plate’ and the ‘Bragg-Berry q-plate’. On the one hand, modal q-plate converts an incidentfundamental Gaussian beam into a Laguerre-Gaussian beam of given radial and azimuthal indices,hence going beyond the capabilities of conventional q-plates that only control the azimuthal degreeof freedom, i.e. the orbital angular momentum content of light. Towards experimental realization ofmodal q-plates, two approaches are developed: one based on artificially nanostructured glasses andanother based on naturally self-organized liquid crystal topological defects. On the other hand,Bragg-Berry q-plate consist of mirror-backed inhomogeneous thin film of chiral liquid crystal(cholesteric) that provides fully efficient spin-orbit beam shaping over broad spectral range of theincident beam, in contrast to the conventional q-plates that are designed for single wavelength.Furthermore, ultra-broadband spin-orbit beam shaping is achieved by inducing an extra modulationof the supramolecular twisted structure of the cholesteric liquid crystal along the propagationdirection. We also show that the presence of a back-mirror allows a powerful spatio-temporal controlof the polarization vectorial properties of the light fields generated by Bragg-Berry q-plate.

Cette thèse étudie le raffinement local de maillage à la fois en espace et en temps pour l’équation de l’elastodynamique du second ordre pour le calcul haute performance. L’objectif est de mettre en place des méthodes numériques pour traiter des hétérogénéités de petite taille ayant un impact important sur la propagation des ondes. Nous utilisons une approche par éléments finis de Galerkin discontinus avec pénalisation pour leur flexibilité et facilité de parallélisation. La formulation éléments finis que nous proposons a pour particularité d’être élasto-acoustique, pour pouvoir prendre en compte des hétérogénéités acoustiques de petite taille. Par ailleurs, nous proposons un terme de pénalisation optimisé qui est mieux adapté à l’équation de l’élastodynamique, conduisant en particulier à une meilleure condition CFL. Nous avons aussi amélioré une formulation PML du second ordre pour laquelle nous avons proposé une nouvelle discrétisation temporelle qui rend la formulation plus stable. En tirant parti de la p-adaptivité et des maillages non-conformes des méthodes de Galerkin discontinues combiné à une méthode de pas de temps local, nous avons grandement réduit le coût du raffinement local. Ces méthodes ont été implémentées en C++, en utilisant des techniques de template metaprogramming, au sein d’un code parallèle à mémoire distribuée (MPI) et partagée (OpenMP). Enfin, nous montrons le potentiel de notre approche sur des cas tests de validation et sur des cas plus réalistes avec des milieux présentant des hydrofractures. / This thesis studies local mesh refinement both in time and space for the second order elastodynamic equation in a high performance computing context. The objective is to develop numerical methods to treat small heterogeneities that have global impact on wave propagation. We use an internal penalty discontinuous Galerkin finite element approach for its flexibity and parallelization capabilities. The elasto-acoustic finite element formulation we discuss is elasto-acoustic in order to handle local acoustic heterogeneities. We also propose an optimized penalty term more suited to the elastodynamic equation that results in better CFL condition. We improve a second order PML formulation with an original time discretization that results in a more stable formulation. Using the p-adaptivity and nonconforming mesh capabilities of discontinuous Galerkin methods combined with a local time stepping method, we greatly reduce the high computational cost of local refinements. These methods have been implemented in C++, using template metaprogramming, in a distributed memory (MPI) and shared memory (OpenMP) parallel code. Finally, we show the potential of our methods on validation test cases and on more realistic test cases with medium including hydrofractures.

With the advancement of technology and the development of more sophisticated remote sensing sensor systems, the use of satellite imagery has opened up various fields of exploration and application. There has been an increased interest in analysis of multi-temporal satellite image in the past few years because of the wide variety of possible applications of in both short-term and long-term image analysis. The type of changes that might be of interest can range from short-term phenomena such as flood assessment and crop growth stage, to long-term phenomena such as urban fringe development. This thesis studies flood assessment and land cover mapping of satellite images, and proposes nature inspired algorithms that can be easily implemented in realistic scenarios. Disaster monitoring using space technology is one of the key areas of research with vast potential; particularly flood based disasters are more challenging. Every year floods occur in many regions of the world and cause great losses. In order to monitor and assess such situations, decision-makers need accurate near real-time knowledge of the field situation. How to provide actual information to decision-makers for effective flood monitoring and mitigation is an important task, from the point of view of public welfare. Over-estimation of the flooded area leads to over-compensation to people, while under-estimation results in production loss and negative impacts on the population. Hence it is essential to assess the flood damage accurately, both in qualitative and quantitative terms. In such situations, land cover maps play a very critical role. Updating land cover maps is a time consuming and costlier operation when it is performed using traditional or manual methods. Hence, there is a need to find solutions for such problem through automation. Design of automatic systems dedicated to satellite image processing which involves change detection to discriminate areas of land cover change between imaging dates. The system integrates the spectral and spatial information with the techniques of image registration and pattern classification using nature inspired techniques. In the literature, various works have been carried out for solving the problem of image registration and pattern classification using conventional methods. Many researchers have proved, for different situations, that nature inspired techniques are promising in comparison with that of conventional methods. The main advantage of nature inspired technique over any other conventional methods is its stochastic nature, which converges to optimal solution for any dynamic variation in a given satellite image. Results are given in such terms as to delineate change in multi-date imagery using change-versus-no-change information to guide multi-date data analysis. The main objective of this study is to analyze spatio-temporal satellite data to bring out significant changes in the land cover map through automated image processing methods. In this study, for satellite image analysis of flood assessment and land cover mapping, the study areas and images considered are: Multi-temporal MODerate-resolution Imaging Spectroradiometer (MODIS) image around Krishna river basin in Andhra Pradesh India; Linear Imaging Self Scanning Sensor III (LISS III)and Synthetic Aperture Radar(SAR)image around Kosi river basin in Bihar, India; Landsat7thematicmapperimage from the southern part of India; Quick-Bird image of the central Bangalore, India; Hyperion image around Meerut city, Uttar Pradesh, India; and Indian pines hyperspectral image. In order to develop a flood assessment framework for this study, a database was created from remotely sensed images (optical and/or Synthetic Aperture Radar data), covering a period of time. The nature inspired techniques are used to find solutions to problems of image registration and pattern classification of a multi-sensor and multi-temporal satellite image. Results obtained are used to localize and estimate accurately the flood extent and also to identify the type of the inundated area based on land cover mapping. The nature inspired techniques used for satellite image processing are Artificial Neural Network (ANN), Genetic Algorithm (GA),Particle Swarm Optimization (PSO), Firefly Algorithm(FA),Glowworm Swarm Optimization(GSO)and Artificial Immune System (AIS). From the obtained results, we evaluate the performance of the methods used for image registration and pattern classification to compare the accuracy of satellite image processing using nature inspired techniques. In summary, the main contributions of this thesis include (a) analysis of flood assessment and land cover mapping using satellite images and (b) efficient image registration and pattern classification using nature inspired algorithms, which are more popular than conventional optimization methods because of their simplicity, parallelism and convergence of the population towards the optimal solution in a given search space.

As a result of increase in global average surface temperature, abnormalities in different hydroclimatic components such as evapotranspiration, stream flow and precipitation have been experienced. So investigation has to be carried out to assess the hidden abnormality subsisting in the hydroclimatological time series in the form of trend. This thesis broadly consists of following four parts. The first part comprises of a detailed review of various trend detection approaches. Approaches incorporating the effect of serial correlation for trend detection and interesting developments concerning various non parametric approaches are focused explicitly. Recent trends in annual, monthly, and seasonl (winter, pre-monsoon, monsoon and post-monsoon) Tmax and Tmin have been analyzed considering three time slots viz. 1901-2003, 1948-2003 and 1970-2003. For this purpose, time series of Tmax and Tmin of India as a whole and for seven homogeneous regions, viz. Western Himalaya (WH), Northwest (NW), Northeast (NE), North Central (NC), East coast (EC), West coast (WC) and Interior Peninsula (IP) were originally considered. During the last three decades significant upward trend in Tmin is found to be present in all regions considered either at annual or seasonal level. Sequential Mann Kendall test revealed that most of the significant upward trends both in Tmax and Tmin began after 1970. The second part discusses about numerous climate models from both Coupled Model Inter comparison Project-5 and 3 (i.e. CMIP5, CMIP3) and their skills in simulating Indian climate and assessing their performance using various evaluation measures. Performances of climate models were evaluated for whole of India and over all the individual grid points covering India. The newly defined metric symbolized as Skill_All is an intersection of the three metrics i.e. Skill_r, Skill_s and Skill_rmse, is used for overall model evaluation analysis. A notable enhancement of Skill_All for CMIP5 over CMIP3 was found. After overall model evaluation study, Compromise Programming, a distance based decision making technique, was employed to rank the GCMs gridwise. Entropy method was employed to obtain weights of the chosen indicators. Group decision making methodology was used to arrive at a consensus based on the ranking pattern obtained by individual grid points. In the third part, a detailed detection and attribution (D&A) analysis is performed to determine the causes of changes in seasonal Tmax and Tmin during the period 1950-2005. This formal D&A exercise helps in providing better insight (than trend detection analysis) into the nature of the observed seasonal temperature changes. It was noticed that the emergence of observed trend was more pronounced in Tmin compared to Tmax. Although observed changes were not solely associated with one specific causative factor, most of the changes in Tmin are above the bounds of natural internal climate variability. Finally in the fourth part, to understand the climate change impact on the hydrological cycle, a spatiotemporal change detection study of potential evapotranspiration (PET) along with Tmax and Tmin over India has been performed. Climatology patterns for PET confirmed a greater PET rate during the month of March, April, May and June. A significant increasing trend in both Tmax and Tmin (Tmin being more) was observed in more number of grid points compared to PET. Significant positive trends in Tmax, Tmin and PET were observed over most of the grid points in the IP region. Heterogeneities existed in the spatiotemporal variability of PET over all India. This spatio-temporal change detection study would be helpful for present and future water resources management.

Dans le domaine de la biologie développementale, un des principaux défis est de comprendre comment des tissus multicellulaires, à l'origine indifférenciés, peuvent engendrer des formes aussi complexes que celles d'une fleur. De part son implication dans l'organogenèse florale, l'auxine est une phytohormone majeure. Nous avons donc déterminé son réseau binaire potentiel, puis y avons appliqué des modèles de clustering de graphes s'appuyant sur les profils de connexion présentés par ces 52 facteurs de transcription (FT). Nous avons ainsi pu identifier trois groupes, proches des groupes biologiques putatifs: les facteurs de réponse à l'auxine activateurs (ARF+), répresseurs (ARF-) et les Aux/IAAs. Nous avons détecté l'auto-interaction des ARF+ et des Aux/IAA, ainsi que leur interaction, alors que les ARF- en présentent un nombre restreint. Ainsi, nous proposons un mode de compétition auxine indépendent entre ARF+ et ARF- pour la régulation transcriptionelle. Deuxièmement, nous avons modélisé l'influence des séquences de dimérisation des FT sur la structure de l'interactome en utilisant des modèles de mélange Gaussien pour graphes aléatoires. Les groupes obtenus sont proches des précédents, et les paramètres estimés nous on conduit à conclure que chaque sous-domaine peut jouer un rôle différent en fonction de leur proximité phylogénétique.Enfin, nous sommes passés à l'échelle multi-cellulaire ou, par un graphe spatio-temporel, nous avons modélisé les premiers stades du développement floral d'A. thaliana. Nous avons pu extraire des caractéristiques cellulaires (3D+t) de reconstruction d'imagerie confocale, et avons démontré la possibilité de caractériser l'identité cellulaire en utilisant des méthodes de classification hiérarchique et des arbres de Markov cachés. / A striking aspect of flowering plants is that, although they seem to display a great diversity of size and shape, they are made of the same basics constituents, that is the cells. The major challenge is then to understand how multicellular tissues, originally undifferentiated, can give rise to such complex shapes. We first investigated the uncharacterised signalling network of auxin since it is a major phytohormone involved in flower organogenesis.We started by determining the potential binary network, then applied model-based graph clustering methods relying on connectivity profiles. We demonstrated that it could be summarise in three groups, closely related to putative biological groups. The characterisation of the network function was made using ordinary differential equation modelling, which was later confirmed by experimental observations.In a second time, we modelled the influence of the protein dimerisation sequences on the auxin interactome structure using mixture of linear models for random graphs. This model lead us to conclude that these groups behave differently, depending on their dimerisation sequence similarities, and that each dimerisation domains might play different roles.Finally, we changed scale to represent the observed early stages of A. thaliana flower development as a spatio-temporal property graph. Using recent improvements in imaging techniques, we could extract 3D+t cellular features, and demonstrated the possibility of identifying and characterising cellular identity on this basis. In that respect, hierarchical clustering methods and hidden Markov tree have proven successful in grouping cell depending on their feature similarities.

Les maladies cardiovasculaires et en particulier les maladies coronariennes représentent la principale cause de mortalité mondiale avec 17,9 millions de décès en 2012. L’IRM cardiaque est un outil particulièrement intéressant pour la compréhension et l’évaluation des cardiopathies, notamment ischémiques. Son apport diagnostique est souvent majeur et elle apporte des informations non accessibles par d’autres modalités d’imagerie. Les travaux menés pendant cette thèse portent plus particulièrement sur l’examen dit de perfusion myocardique qui consiste à étudier la distribution d’un agent de contraste au sein du muscle cardiaque lors de son premier passage. En pratique clinique cet examen est souvent limité à la seule analyse visuelle du clinicien qui recherche un hyposignal lui permettant d’identifier l’artère coupable et d’en déduire le territoire impacté. Cependant, cette technique est relative et ne permet pas de quantifier le flux sanguin myocardique. Au cours de ces dernières années, un nombre croissant de techniques sont apparues pour permettre cette quantification et ce à toutes les étapes de traitement, depuis l’acquisition jusqu’à la mesure elle-même. Nous avons dans un premier temps établi un pipeline de traitement afin de combiner ces approches et de les évaluer à l’aide d’un fantôme numérique et à partir de données cliniques. Nous avons pu démontrer que l’approche Bayésienne permettait de quantifier la perfusion cardiaque et sa supériorité à évaluer le délai d’arrivé du bolus d’indicateur par rapport au modèle de Fermi. De plus l’approche Bayésienne apporte en supplément des informations intéressantes telles que la fonction de densité de probabilité de la mesure et l’incertitude sur la fonction résidu qui permettent de connaitre la fiabilité de la mesure effectuée notamment en observant la répartition de la fonction de densité de probabilité de la mesure. Enfin, nous avons proposé un algorithme de segmentation des lésions myocardiques, exploitant les dimensions spatiotemporelles des données de perfusion. Cette technique permet une segmentation objective et précise de la région hypoperfusée permettant une mesure du flux sanguin myocardique sur une zone de tissu dont le comportement est homogène et dont la mesure du signal moyen permet une augmentation du rapport contraste à bruit. Sur la cohorte de 30 patients, la variabilité des mesures du flux sanguin myocardique effectuées sur les voxels détectés par cette technique était significativement inférieure à celle des mesures effectuées sur les voxels des zones définies manuellement (différence moyenne=0.14, 95% CI [0.07, 0.2]) et de celles effectuées sur les voxels des zones définies à partir de la méthode bullseye (différence moyenne =0.25, 95% CI [0.17, 0.36]) / Cardiovascular diseases and in particular coronary heart disease are the main cause of death worldwide with 17.9 million deaths in 2012. Cardiac MRI is a particularly interesting tool for understanding and evaluating heart disease, including ischemic heart disease. Its diagnostic contribution is often major and it provides information that is not accessible by other imaging modalities. The work carried out during this thesis focuses more specifically on the so-called myocardium perfusion test, which consists in studying the distribution of a contrast agent within the heart muscle during its first passage. In clinical practice, this examination is often limited to the clinician's visual analysis, allowing him to identify the culprit artery and deduce the impacted territory. However, this technique is relative and does not quantify myocardial blood flow. In recent years, an increasing number of techniques have emerged to enable this quantification at all stages of processing, from acquisition to the measurement itself. We first established a treatment pipeline to combine these approaches and evaluate them using a digital phantom and clinical data. We demonstrated that the Bayesian approach is able to quantify myocardium perfusion and its superiority in evaluating the arrival time of the indicator bolus compared to the Fermi model. In addition, the Bayesian approach provides additional interesting information such as the probability density function of the measurement and the uncertainty of the residual function, which makes it possible to know the reliability of the measurement carried out, in particular by observing the distribution of the probability density function of the measurement. Finally, we proposed an algorithm for segmentation of myocardial lesions, using the spatial and temporal dimensions of infusion data. This technique allows an objective and precise segmentation of the hypoperfused region allowing a measurement of myocardial blood flow over an area of tissue which behavior is homogeneous and which average signal measurement allows an increase in the contrast-to-noise ratio. In the cohort of 30 patients, the variability of myocardial blood flow measurements performed on voxels detected by this technique was significantly lower than that of measurements performed on voxels in manually defined areas (mean difference=0.14, 95% CI[0.07, 0.2]) and those performed on voxels in areas defined using the bullseye method (mean difference=0.25, 95% CI[0.17, 0.36])

This thesis deals with knowledge discovery in spatio-temporal data, which is currently a rapidly evolving area of research in information technology. First, it describes the general principles of knowledge discovery, then, after a brief introduction to mining in the temporal and spatial data, it focuses on the overview and description of existing methods for mining in spatio-temporal data. It focuses, in particular, on moving objects data in the form of trajectories with an emphasis on the methods for trajectory outlier detection. The next part of the thesis deals with the process of implementation of the trajectory outlier detection algorithm called TOP-EYE. In order to testing, validation and possibility of using this algorithm is designed and implemented an application for trajectory outlier detection. The algorithm is experimentally evaluated on two different data sets.