L'imagerie médicale joue désormais un rôle central tant en recherche fondamentale sur le développement des maladies que dans l'aide au diagnostic des pathologies. Il existe plusieurs techniques ou modalités d'imagerie qui permettent de visualiser de façon non invasive des corps biologiques et d'en fournir leurs propriétés structurelles et fonctionnelles. Un des problèmes majeurs rencontré est de pouvoir analyser et traiter ces techniques d'imagerie dans un référentiel commun. Ce problème, connu sous le nom de recalage ou registration, consiste en une estimation d'une transformation géométrique permettant la superposition spatiale des caractéristiques correspondantes entre les images. Deux contextes d'application peuvent être distingués : Le recalage monomodal qui traite les séquences temporelles d'images provenant de la même modalité et le recalage multimodal qui traite la mise en correspondance d'images venant de différentes modalités. Le laboratoire TomOptUs de l'Université de Sherbrooke a développé un lit multimodal, avec marqueurs fiduciaux, destiné à accueillir un petit animal pour des prises de mesures avec différentes modalités. Il est donc intéressant de recaler ces modalités en utilisant l'information basée sur les attributs géométriques ou sur l'intensité des pixels ou voxels. Le laboratoire a aussi développé un système laser-scanner permettant de mesurer le relief d'un objet ou d'un animal afin d'obtenir des images profilométriques. Avec ces images, il devient possible de faire un recalage de surface avec d'autres modalités d'imagerie dans la mesure où on veut obtenir le profil extérieur de l'animal afin de faire une reconstruction interne 3D. Le cadre de cette recherche consiste à développer un programme informatique permettant de répondre au besoin du laboratoire en matière de recalage d'image à l'aide de marqueurs fiduciaux et de recalage d'images profilométriques. Le présent document couvre la théorie et les algorithmes utilisés ainsi que la conception informatique détaillée permettant d'obtenir des résultats concluants.

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Notre travail s'inscrit dans le domaine de l'affective computing et plus précisément la modélisation, détection et annotation des émotions. L'objectif est d'étudier, d'identifier et de modéliser les émotions afin d'assurer l’échange entre applications multimodales. Notre contribution s'axe donc sur trois points. En premier lieu, nous présentons une nouvelle vision de la modélisation des états émotionnels basée sur un modèle générique pour la représentation et l'échange des émotions entre applications multimodales. Il s'agit d'un modèle de représentation hiérarchique composé de trois couches distinctes : la couche psychologique, la couche de calcul formel et la couche langage. Ce modèle permet la représentation d'une infinité d'émotions et la modélisation aussi bien des émotions de base comme la colère, la tristesse et la peur que les émotions complexes comme les émotions simulées et masquées. Le second point de notre contribution est axé sur une approche monomodale de reconnaissance des émotions fondée sur l'analyse des signaux physiologiques. L'algorithme de reconnaissance des émotions s'appuie à la fois sur l'application des techniques de traitement du signal, sur une classification par plus proche voisins et également sur notre modèle multidimensionnel de représentation des émotions. Notre troisième contribution porte sur une approche multimodale de reconnaissance des émotions. Cette approche de traitement des données conduit à une génération d'information de meilleure qualité et plus fiable que celle obtenue à partir d'une seule modalité. Les résultats expérimentaux montrent une amélioration significative des taux de reconnaissance des huit émotions par rapport aux résultats obtenus avec l'approche monomodale. Enfin nous avons intégré notre travail dans une application de détection de la dépression des personnes âgées dans un habitat intelligent. Nous avons utilisé les signaux physiologiques recueillis à partir de différents capteurs installés dans l'habitat pour estimer l'état affectif de la personne concernée. / This study focuses on affective computing in both fields of modeling and detecting emotions. Our contributions concern three points. First, we present a generic solution of emotional data exchange between heterogeneous multi-modal applications. This proposal is based on a new algebraic representation of emotions and is composed of three distinct layers : the psychological layer, the formal computational layer and the language layer. The first layer represents the psychological theory adopted in our approach which is the Plutchik's theory. The second layer is based on a formal multidimensional model. It matches the psychological approach of the previous layer. The final layer uses XML to generate the final emotional data to be transferred through the network. In this study we demonstrate the effectiveness of our model to represent an in infinity of emotions and to model not only the basic emotions (e.g., anger, sadness, fear) but also complex emotions like simulated and masked emotions. Moreover, our proposal provides powerful mathematical tools for the analysis and the processing of these emotions and it enables the exchange of the emotional states regardless of the modalities and sensors used in the detection step. The second contribution consists on a new monomodal method of recognizing emotional states from physiological signals. The proposed method uses signal processing techniques to analyze physiological signals. It consists of two main steps : the training step and the detection step. In the First step, our algorithm extracts the features of emotion from the data to generate an emotion training data base. Then in the second step, we apply the k-nearest-neighbor classifier to assign the predefined classes to instances in the test set. The final result is defined as an eight components vector representing the felt emotion in multidimensional space. The third contribution is focused on multimodal approach for the emotion recognition that integrates information coming from different cues and modalities. It is based on our proposed formal multidimensional model. Experimental results show how the proposed approach increases the recognition rates in comparison with the unimodal approach. Finally, we integrated our study on an automatic tool for prevention and early detection of depression using physiological sensors. It consists of two main steps : the capture of physiological features and analysis of emotional information. The first step permits to detect emotions felt throughout the day. The second step consists on analyzing these emotional information to prevent depression.

This master’s thesis gives a description of fundus camera as a medical imaging system. Sub features of this system are explained in short, thus examples of certain construction variants are given. Furthermore, the work deals with image fusion and associated possibilities of digital image processing. One set of consecutive scanned images of human eye’s retina has been provided for the practical part of this work. During program processing of these data, decomposition of obtained images to single-color sequences is performed. For these partial monochromatic sequences, monomodal registration is performed, based on calculation of the brightness similarity criterion between the pairs of images. From the three created monochromatic sequences of registered images, new sequence of color images is created, using multimodal registration of each image triples. As a basis for similarity evaluation during multimodal registration, an information similarity criterion was used.

The diploma thesis deals with registration and analysis of images from the experimental low-cost fundus camera that reaches a low SNR (around 10 dB) and low temporal and spatial resolution. The aim of the diploma tesis is to explore the possibilities of digital processing leading to the creation of a videosequence that has real benefits for medical diagnostics. The well-known program elastix is used for registration. Preprocessing filters and interpolation are implemented in Matlab. The program provides a wide range of setting options, out of which many combinations were tested and evaluated. To assess the accuracy achieved, spatial variations in the detected motion of blood-vessels are evaluated. Best results with a precision below 0.3 px were achieved by using a band-pass filter, a~suitably sized mask, rigid registration and a metric of the mutual information. Test sequences were registered precisely enough both for visual assessment and basic computational analysis. Registered sequences and the developed application that both can be used in the further development of the experimental camera are the main contributions of the diploma thesis.

The multiliteracies pedagogy of the New London Group is a response to the emergence of new literacies and changing forms of meaning-making in contemporary contexts of increased cultural and linguistic diversity. This critical ethnographic research investigates the interactions between pedagogy, power, discourses, and differential access to multiliteracies, among a group of culturally and linguistically diverse learners in a mainstream Australian classroom. The study documents the way in which a teacher enacted the multiliteracies pedagogy through a series of mediabased lessons with her year six (aged 11-12 years) class. The reporting of this research is timely because the multiliteracies pedagogy has become a key feature of Australian educational policy initiatives and syllabus requirements. The methodology of this study was based on Carspecken's critical ethnography. This method includes five stages: Stage One involved eighteen days of observational data collection over the course of ten weeks in the classroom. The multiliteracies lessons aimed to enable learners to collaboratively design a claymation movie. Stage Two was the initial analysis of data, including verbatim transcribing, coding, and applying analytic tools to the data. Stage Three involved semi-structured, forty-five minute interviews with the principal, teacher, and four culturally and linguistically diverse students. In Stages Four and Five, the results of micro-level data analysis were compared with macro-level phenomena using structuration theory and extant literature about access to multiliteracies. The key finding was that students' access to multiliteracies differed among the culturally and linguistically diverse group. Existing degrees of access were reproduced, based on the learners' relation to the dominant culture. In the context of the media-based lessons in which students designed claymation movies, students from Anglo-Australian, middle-class backgrounds had greater access to transformed designing than those who were culturally marginalised. These experiences were mediated by pedagogy, power, and discourses in the classroom, which were in turn influenced by the agency of individuals. The individuals were both enabled and constrained by structures of power within the school and the wider educational and social systems. Recommendations arising from the study were provided for teachers, principals, policy makers and researchers who seek to monitor and facilitate the success of the multiliteracies pedagogy in culturally and linguistically diverse educational contexts.