Os músculos extraoculares (EOM), responsáveis pelas rotações oculares, apresentam-se aumentados em suas dimensões na orbitopatia de Graves, o que pode levar o paciente à cegueira (neuropatia óptica). Na prática clínica normalmente mede-se manualmente, em cada imagem coronal de tomografia computadorizada por raios-X (CT), o diâmetro desses músculos para avaliar se estes estão aumentados. A subjetividade e o tempo consumido na aquisição destas medidas são as principais deficiências desses métodos manuais. Dessa forma, apresentamos um método de segmentação dos EOM (MSEG) que supera as falhas, acima citadas. O MSEG proposto é baseado no detector de bordas Laplaciano da Gaussiana (LoG) associado à morfologia matemática. Para determinação do tamanho da máscara LoG levou-se em consideração os efeitos devido ao truncamento e a amostragem. A acurácia das medidas em modelos tridimensionais (3D) é afetada pelo efeito de volume parcial (PVE). Em CT, por exemplo, falsas estruturas de tecidos moles aparecem nas interfaces do osso-para-gordura e do osso-para-ar. Além disso, a pele, que tem número CT (ou escala de Hounsfield) idêntico ao tecido mole, obscurece a renderização deste. A fim de produzir imagens 3D do osso e dos tecidos moles, mais confiáveis para medidas e com melhora de qualidade, foram desenvolvidos dois métodos de classificação dos voxels com PVE (MCLA) baseados num novo modelo de mistura. A remoção da pele é realizada por meio da morfologia matemática. Renderizações volumétricas foram criadas, antes e depois de aplicar os MCLA. Experimentos qualitativo e quantitativo foram conduzidos utilizando fantons matemáticos que simularam diferentes níveis de PVE por adição de ruído e borramento e em dados clínicos de CT. O resultado em 218 pares de medidas de áreas dos EOM realizadas em imagens coronais de CT (3 normais e 2 Graves) revelou uma boa correlação (R=0,92) entre o MSEG e o traçado manual. A medida de taxa de ocupação dos EOM na órbita (TO) feita em 33 pacientes (5 normais e 28 Graves) apresentou o maior valor no grupo Graves com neuropatia óptica, TO=34,3%. Este valor é quase cinco vezes maior que o grupo normal, TO=7,3%. Todos os resultados demonstraram uma melhora de qualidade das imagens 3D depois da aplicação dos MCLA. A análise quantitativa indica que mais de 98% dos voxels com PVE foram removidos por ambos MCLA, e o segundo MCLA têm um desempenho um pouco melhor que o primeiro. Além disso, a remoção da pele torna vívidos os finos detalhes nas estruturas musculares. Medidas em modelos 3D devem ser tomadas com cuidado na radiologia em vista dos artefatos demonstrados neste trabalho, artefatos vindos, principalmente, do PVE. Em nossos experimentos, os erros nas medidas de volume dos EOM foram acima de 25% do valor estimado como "verdadeiro". Imagens volumétricas com PVE resolvidos são apresentadas, e assim medidas mais acuradas são asseguradas. / The extraocular muscles (EOM), which are responsible for the eyes movements, are presented enlarged in their dimensions in Graves’ orbitopathy. These deformations can lead patients to blindness. In clinical routine, physicians normally evaluate, in computer tomography (CT) images, the diameter of the EOM by manual tracing to check if they are enlarged. However, the accuracy of the EOM measurements is impaired by the subjectivity of these manual methods. Further, the time consuming is also one of the main drawbacks on these methods. This way we present an EOM segmentation method (MSEG) that overcomes the difficulties pointed above. The MSEG method is based on the Laplacian-of-Gaussian operator (LOG) combined with the mathematical morphology theory. We have taken into account the effect of discretization and numerical truncation during the LOG implementation. In CT, partial volume effects (PVE) cause several artifacts in volume rendering. In order to create 3D rendition more reliable to carry out anatomical measures and also to pursue superior quality of display of both soft-tissue and bone, we introduce two methods for detecting and classifying voxels with PVE (MCLA) based on a new approach. A method is described to automatically peel skin so that PVE-resolved renditions of bone and soft-tissue reveal considerably more details. We have conducted experiments to evaluate quantitatively and qualitatively all methods proposed here. The MSEG method is well correlated with manual tracing in our experiments (R=0,92). Surface renditions are created from EOM CT dataset segmented using the MSEG method. We have also conducted a quantitative evaluation in patients with Graves’ orbitopathy wherein the EOM volume ratio in the orbit (TO) was T=34,3%, which is about five times higher than in normal patient (TO=7,3%). Volume renditions have been created before and after applying the methods for several patient CT datasets. A mathematical phantom experiment involving different levels of PVE has been conducted by adding different degrees of noise and blurring. A quantitative evaluation was performed using the mathematical phantom and clinical CT data wherein an operator carefully masked out voxels with PVE in the segmented images. All results have demonstrated the enhanced quality of display of bone and soft tissue after applying the proposed methods. The quantitative evaluations indicate that more than 98% of the voxels with PVE are removed by the two methods and the second method performs slightly better than the first. Further, skin peeling vividly reveals fine details in the soft tissue structures. 3D renditions should be used with care in radiology in view of artifacts demonstrated in this work coming from PVE. Finally, we have estimated volume errors in the EOM models higher than 25% if PVE is not properly handled.

Os músculos extraoculares (EOM), responsáveis pelas rotações oculares, apresentam-se aumentados em suas dimensões na orbitopatia de Graves, o que pode levar o paciente à cegueira (neuropatia óptica). Na prática clínica normalmente mede-se manualmente, em cada imagem coronal de tomografia computadorizada por raios-X (CT), o diâmetro desses músculos para avaliar se estes estão aumentados. A subjetividade e o tempo consumido na aquisição destas medidas são as principais deficiências desses métodos manuais. Dessa forma, apresentamos um método de segmentação dos EOM (MSEG) que supera as falhas, acima citadas. O MSEG proposto é baseado no detector de bordas Laplaciano da Gaussiana (LoG) associado à morfologia matemática. Para determinação do tamanho da máscara LoG levou-se em consideração os efeitos devido ao truncamento e a amostragem. A acurácia das medidas em modelos tridimensionais (3D) é afetada pelo efeito de volume parcial (PVE). Em CT, por exemplo, falsas estruturas de tecidos moles aparecem nas interfaces do osso-para-gordura e do osso-para-ar. Além disso, a pele, que tem número CT (ou escala de Hounsfield) idêntico ao tecido mole, obscurece a renderização deste. A fim de produzir imagens 3D do osso e dos tecidos moles, mais confiáveis para medidas e com melhora de qualidade, foram desenvolvidos dois métodos de classificação dos voxels com PVE (MCLA) baseados num novo modelo de mistura. A remoção da pele é realizada por meio da morfologia matemática. Renderizações volumétricas foram criadas, antes e depois de aplicar os MCLA. Experimentos qualitativo e quantitativo foram conduzidos utilizando fantons matemáticos que simularam diferentes níveis de PVE por adição de ruído e borramento e em dados clínicos de CT. O resultado em 218 pares de medidas de áreas dos EOM realizadas em imagens coronais de CT (3 normais e 2 Graves) revelou uma boa correlação (R=0,92) entre o MSEG e o traçado manual. A medida de taxa de ocupação dos EOM na órbita (TO) feita em 33 pacientes (5 normais e 28 Graves) apresentou o maior valor no grupo Graves com neuropatia óptica, TO=34,3%. Este valor é quase cinco vezes maior que o grupo normal, TO=7,3%. Todos os resultados demonstraram uma melhora de qualidade das imagens 3D depois da aplicação dos MCLA. A análise quantitativa indica que mais de 98% dos voxels com PVE foram removidos por ambos MCLA, e o segundo MCLA têm um desempenho um pouco melhor que o primeiro. Além disso, a remoção da pele torna vívidos os finos detalhes nas estruturas musculares. Medidas em modelos 3D devem ser tomadas com cuidado na radiologia em vista dos artefatos demonstrados neste trabalho, artefatos vindos, principalmente, do PVE. Em nossos experimentos, os erros nas medidas de volume dos EOM foram acima de 25% do valor estimado como "verdadeiro". Imagens volumétricas com PVE resolvidos são apresentadas, e assim medidas mais acuradas são asseguradas. / The extraocular muscles (EOM), which are responsible for the eyes movements, are presented enlarged in their dimensions in Graves’ orbitopathy. These deformations can lead patients to blindness. In clinical routine, physicians normally evaluate, in computer tomography (CT) images, the diameter of the EOM by manual tracing to check if they are enlarged. However, the accuracy of the EOM measurements is impaired by the subjectivity of these manual methods. Further, the time consuming is also one of the main drawbacks on these methods. This way we present an EOM segmentation method (MSEG) that overcomes the difficulties pointed above. The MSEG method is based on the Laplacian-of-Gaussian operator (LOG) combined with the mathematical morphology theory. We have taken into account the effect of discretization and numerical truncation during the LOG implementation. In CT, partial volume effects (PVE) cause several artifacts in volume rendering. In order to create 3D rendition more reliable to carry out anatomical measures and also to pursue superior quality of display of both soft-tissue and bone, we introduce two methods for detecting and classifying voxels with PVE (MCLA) based on a new approach. A method is described to automatically peel skin so that PVE-resolved renditions of bone and soft-tissue reveal considerably more details. We have conducted experiments to evaluate quantitatively and qualitatively all methods proposed here. The MSEG method is well correlated with manual tracing in our experiments (R=0,92). Surface renditions are created from EOM CT dataset segmented using the MSEG method. We have also conducted a quantitative evaluation in patients with Graves’ orbitopathy wherein the EOM volume ratio in the orbit (TO) was T=34,3%, which is about five times higher than in normal patient (TO=7,3%). Volume renditions have been created before and after applying the methods for several patient CT datasets. A mathematical phantom experiment involving different levels of PVE has been conducted by adding different degrees of noise and blurring. A quantitative evaluation was performed using the mathematical phantom and clinical CT data wherein an operator carefully masked out voxels with PVE in the segmented images. All results have demonstrated the enhanced quality of display of bone and soft tissue after applying the proposed methods. The quantitative evaluations indicate that more than 98% of the voxels with PVE are removed by the two methods and the second method performs slightly better than the first. Further, skin peeling vividly reveals fine details in the soft tissue structures. 3D renditions should be used with care in radiology in view of artifacts demonstrated in this work coming from PVE. Finally, we have estimated volume errors in the EOM models higher than 25% if PVE is not properly handled.

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This dissertation provides empirical evidence for the effects of the fidelity of VR system components, and novel 3D interaction techniques for analyzing volume datasets. It provides domain-independent results based on an abstract task taxonomy for visual analysis of scientific datasets. Scientific data generated through various modalities e.g. computed tomography (CT), magnetic resonance imaging (MRI), etc. are in 3D spatial or volumetric format. Scientists from various domains e.g., geophysics, medical biology, etc. use visualizations to analyze data. This dissertation seeks to improve effectiveness of scientific visualizations. Traditional volume data analysis is performed on desktop computers with mouse and keyboard interfaces. Previous research and anecdotal experiences indicate improvements in volume data analysis in systems with very high fidelity of display and interaction (e.g., CAVE) over desktop environments. However, prior results are not generalizable beyond specific hardware platforms, or specific scientific domains and do not look into the effectiveness of 3D interaction techniques. We ran three controlled experiments to study the effects of a few components of VR system fidelity (field of regard, stereo and head tracking) on volume data analysis. We used volume data from paleontology, medical biology and biomechanics. Our results indicate that different components of system fidelity have different effects on the analysis of volume visualizations. One of our experiments provides evidence for validating the concept of Mixed Reality (MR) simulation. Our approach of controlled experimentation with MR simulation provides a methodology to generalize the effects of immersive virtual reality (VR) beyond individual systems. To generalize our (and other researchers') findings across disparate domains, we developed and evaluated a taxonomy of visual analysis tasks with volume visualizations. We report our empirical results tied to this taxonomy. We developed the Volume Cracker (VC) technique for improving the effectiveness of volume visualizations. This is a free-hand gesture-based novel 3D interaction (3DI) technique. We describe the design decisions in the development of the Volume Cracker (with a list of usability criteria), and provide the results from an evaluation study. Based on the results, we further demonstrate the design of a bare-hand version of the VC with the Leap Motion controller device. Our evaluations of the VC show the benefits of using 3DI over standard 2DI techniques. This body of work provides the building blocks for a three-way many-many-many mapping between the sets of VR system fidelity components, interaction techniques and visual analysis tasks with volume visualizations. Such a comprehensive mapping can inform the design of next-generation VR systems to improve the effectiveness of scientific data analysis. / Ph. D.

Les données de sismique réflexion sont une source d'information essentielle pour la modélisation tridimensionnelle des structures du sous-sol dans l'exploration-production des hydrocarbures. Ce travail vise à fournir des outils de visualisation pour leur interprétation. Les défis à relever sont à la fois d'ordre qualitatif et quantitatif. Il s'agit en effet de considérer (1) la nature particulière des données et la démarche d'interprétation (2) la taille des données. Notre travail s'est donc axé sur ces deux aspects : 1) Du point de vue qualitatif, nous mettons tout d'abord en évidence les principales caractéristiques des données sismiques, ce qui nous permet d'implanter une technique de visualisation volumique adaptée. Nous abordons ensuite l'aspect multimodal de l'interprétation qui consiste à combiner plusieurs sources d'information (sismique et structurale). Selon la nature de ces sources (strictement volumique ou volumique et surfacique), nous proposons deux systèmes de visualisation différents. 2) Du point de vue quantitatif, nous définissons tout d'abord les principales contraintes matérielles intervenant dans l'interprétation, ce qui nous permet d'implanter un système générique de gestion de la mémoire. Initialement destiné au couplage de la visualisation et des calculs sur des données volumiques massives, il est ensuite amélioré et spécialisé pour aboutir à un système dynamique de gestion distribuée de la mémoire sur cluster de PCs. Cette dernière version, dédiée à la visualisation, permet de manipuler des données sismiques à échelle régionale (100-200 Go) en temps réel. Les problématiques sont abordées à la fois dans le contexte scientifique de la visualisation et dans le contexte d'application des géosciences et de l'interprétation sismique / Seismic reflection data are a valuable source of information for the three-dimensional modeling of subsurface structures in the exploration-production of hydrocarbons. This work focuses on the implementation of visualization techniques for their interpretation. We face both qualitative and quantitative challenges. It is indeed necessary to consider (1) the particular nature of seismic data and the interpretation process (2) the size of data. Our work focuses on these two distinct aspects : 1) From the qualitative point of view, we first highlight the main characteristics of seismic data. Based on this analysis, we implement a volume visualization technique adapted to the specificity of the data. We then focus on the multimodal aspect of interpretation which consists in combining several sources of information (seismic and structural). Depending on the nature of these sources (strictly volumes or both volumes and surfaces), we propose two different visualization systems. 2) From the quantitative point of view, we first define the main hardware constraints involved in seismic interpretation. Focused on these constraints, we implement a generic memory management system. Initially able to couple visualization and data processing on massive data volumes, it is then improved and specialised to build a dynamic system for distributed memory management on PC clusters. This later version, dedicated to visualization, allows to manipulate regional scale seismic data (100-200 GB) in real-time. The main aspects of this work are both studied in the scientific context of visualization and in the application context of geosciences and seismic interpretation

Les Moments ont été largement utilisés dans la reconnaissance de formes et dans le traitement d'image. Dans cette thèse, nous concentrons notre attention sur les 3D moments orthogonaux de Gauss-Hermite, les moments invariants 2D et 3D de Gauss-Hermite, l'algorithme rapide de l'attribut de cohérence et les applications de l'interprétation sismique en utilisant la méthode des moments.Nous étudions les méthodes de suivi automatique d'horizon sismique à partir de moments de Gauss-Hermite en cas de 1D et de 3D. Nous introduisons une approche basée sur une étude multi-échelle des moments invariants. Les résultats expérimentaux montrent que la méthode des moments 3D de Gauss-Hermite est plus performante que les autres algorithmes populaires.Nous avons également abordé l'analyse des faciès sismiques basée sur les caractéristiques du vecteur à partir des moments 3D de Gauss -Hermite, et la méthode de Cartes Auto-organisatrices avec techniques de visualisation de données. L'excellent résultat de l'analyse des faciès montre que l'environnement intégré donne une meilleure performance dans l'interprétation de la structure des clusters.Enfin, nous introduisons le traitement parallèle et la visualisation de volume. En profitant des nouvelles performances par les technologies multi-threading et multi-cœurs dans le traitement et l'interprétation de données sismiques, nous calculons efficacement des attributs sismiques et nous suivons l'horizon. Nous discutons également l'algorithme de rendu de volume basé sur le moteur Open-Scene-Graph qui permet de mieux comprendre la structure de données sismiques. / Moments have been extensively used in pattern recognition and image processing. In this thesis, we focus our attention on the study of 3D orthogonal Gaussian-Hermite moments, 2D and 3D Gaussian-Hermite moment invariants, fast algorithm of coherency attribute, and applications of seismic interpretation using moments methodology.We conduct seismic horizon auto-tracking methods from Gaussian-Hermite moments and moment invariants. We introduce multi-scale moment invariants approach. The experimental results show that method of 3D Gaussian-Hermite moments performs better than the most popular methods.We also approach seismic facies analysis based on feature vectors from 3D Gaussian-Hermite moments, and Self-Organizing Maps method with data visualization techniques. The excellent result shows that the integrated environment gives the best performance in interpreting the correct cluster structure.Finally, we introduce the parallel processing and volume visualization. Taking advantage of new performances by multi-threading and multi-cores technologies into seismic interpretation, we efficiently compute the seismic attributes and track the horizon. We also discuss volume rendering algorithm based on Open-Scene-Graph engine which provides better insight into the structure of seismic data.