Amphiphiles that possess a dual character, hydrophobic and hydrophilic, are employed in many chemical, pharmaceutical and biological applications. Amphiphile molecules that include a hydrophilic head and a hydrophobic tail can easily adsorb at a liquid/vapour interface, to reach to a minimum free energy and hence a most thermodynamically stable state. Surface tension is a key parameter for understanding such behavior of an amphiphile, or a surfactant. This thesis represents a comprehensive study on adsorption and surface tension of slightly volatile, organic amphiphiles in aqueous solution. Although for a vapor-liquid interface, adsorption from both liquid and vapor phases should be considered, they have been almost always considered exclusive of one another. When a volatile surfactant is dissolved in the liquid phase, it also applies a finite partial pressure in the vapor phase. Recently, dynamic surface tension experiments showed that adsorption from both sides of a vapor/liquid interface must be studied simultaneously. It is noted that surface tension phenomena are often dynamic, in particular when the surface under consideration is perturbed. With the newly discovered importance of adsorption from both sides of a vapor/liquid interface, one may have to ask the question: how dynamic surface tension is influenced and responding to the surface perturbation and environment changes, and whether both sides of the interface play a role in surface tension responses. In this research, axisymmetric drop shape analysis-profile (ADSA-P) is used for surface tension measurement. The experiments are performed in a closed chamber where the effects of surfactant concentrations of both liquid and vapor phases on the surface tension can be studied. The partial vapor pressure of surfactant is controlled with an environment solution containing the same surfactant as the sample solution. The environment solution is to facilitate adsorption from the vapor side of the interface by creating a surfactant vapor phase. The effects of surface perturbation, environment condition (i.e., temperature and pressure) and carbon chain length on the surface tension and adsorption kinetics are studied in detail. The surface tension response of 1-octanol aqueous solution to surface area perturbation is investigated. Upon surface compression, the surface tension decreases followed by a gradual increase back to the value prior to compression. On surface expansion, two categories of surface tension response are observed: First, when the change in surface area is smaller than 5%, the behavior similar to that of conventional surfactants is observed. The surface tension increases followed by a gradual decrease back to the value prior to expansion. Second, when the change in surface area is greater than 5%, and the drop concentration is sufficiently larger than the environment concentration, the surface tension initially slightly increases, but after a time delay, it sharply decreases, followed by a gradual increase back to the value prior to expansion. Previous studies showed that at steady-state condition a network of hydrogen bonding between surfactant and water molecules near the surface is created. The unique surface tension response after large expansion might be related to the momentarily destruction of this hydrogen bonding network and gradually making a new one. The effect of temperature on the surface tension and adsorption kinetics of 1-octanol, 1-hexanol and 1-butanol aqueous solutions is studied. The steady-state surface tension is found to decrease upon an increase in temperature, and a linear relationship is observed between them. The modified Langmuir equation of state and the modified kinetic transfer equation are used to model the experimental data of the steady-state and dynamic (time-dependent) surface tension, respectively. The equilibrium constants and adsorption rate constants are evaluated through a minimization procedure for temperatures ranging from 10°C to 35°C. From the steady-state modelling, the equilibrium constants for adsorption from vapor phase and liquid phase are found to increase with temperature. From the dynamic modelling, the adsorption rate constants for adsorption from vapor phase and liquid phase are found to increase with temperature too. The influence of carbon dioxide pressure on the surface tension and adsorption kinetics of the aforementioned surfactant aqueous solutions is investigated. To consider the effect of adsorption/desorption of the two species (surfactant and carbon dioxide) from both sides of a vapor/liquid interface on the surface tension, the modified Langmuir equation of state and the modified kinetic transfer equation are derived. The steady-state and dynamic surface tension data are modelled using the modified Langmuir equation of state and the modified kinetic transfer equation, respectively. The equilibrium constants and adsorption rate constants of surfactant and carbon dioxide are evaluated through a minimization procedure for CO2 pressures ranging from 0 to 690 KPa. From the steady-state modelling, the equilibrium parameters for surfactant and carbon dioxide adsorption from vapor phase and liquid phase are found unchanged for different pressures of carbon dioxide. From the dynamic modelling, the adsorption rate constants for surfactant and carbon dioxide are found to decrease with carbon dioxide pressure. The role of carbon chain length of amphiphiles in aqueous solution is also studied. It is illustrated that the equilibrium constants for adsorption from both sides of a vapor/liquid interface increase from 1-butanol to 1-octanol. The modelling results show that the ratio of the equilibrium constant for adsorption from vapor phase to the equilibrium constant for adsorption from liquid phase declines from 260 to 26 as the chain length is increased from 1-butanol to 1-octanol. Therefore, the contribution to adsorption from liquid phase augments as the chain length is increased. The adsorption kinetics for this group of short carbon chain surfactants is modelled using a kinetic transfer equation. The modelling results show that the adsorption rate constants from vapor phase and liquid phase (kag and kal) increase from 1-butanol to 1-octanol. Steady-state and dynamic modelling also reveals that the maximum surface concentration increases with carbon chain length. These results may be due to the higher hydrophobicity character of a surfactant molecule at longer carbon chain length.

In this thesis, we propose and evaluate two novel scale-based decomposable representations of shape for the segmentation and morphometric analysis of anatomical structures in medical imaging. We propose two representations that are adapted to a particular class of anatomical structures and allow for a richer shape description and a more fine-grained control over the deformation of models based on these representations, when compared to previous techniques. In the first part of this thesis, we introduce the concept of a scale-space shape filter for implicit shape representations that measures the deviation from a tubular shape in a local neighborhood of points, given a particular scale of analysis. We use these filters for the segmentation of blood vessels, and introduce the notion of segmentation with a soft shape prior, where the segmented model is not globally constrained to a predefined shape space, but is penalized locally if it deviates strongly from a tubular structure. Using this filter, we derive a region-based active contour segmentation algorithm for tubular structures that penalizes leakages. We present results on synthetic and real 2D and 3D datasets. In the second part of this thesis, we present a novel multi-scale parametric shape representation using spherical wavelets. Our proposed shape representation encodes shape variations in a population at various scales to be used as prior in a probabilistic segmentation framework. We derive a probabilistic active surface segmentation algorithm using the multi-scale prior coefficients as parameters for our optimization procedure. One nice benefit of this algorithm is that the optimization method can be applied in a coarse-to-fine manner. We present results on 3D sub-cortical brain structures. We also present a novel method of statistical surface-based morphometry based on the use of non-parametric permutation tests and the spherical wavelet shape representation. As an application, we analyze two sub-cortical brain structures, the caudate nucleus and hippocampus.

Medical image analysis aims at developing techniques to extract information from medical images. Among its many sub-fields, image registration and segmentation are two important topics. In this report, we present four pieces of work, addressing different problems as well as coupling them into a unified framework of shape based image segmentation. Specifically: 1. We link the image registration with the point set registration, and propose a globally optimal diffeomorphic registration technique for point set registration. 2. We propose an image segmentation technique which incorporates the robust statistics of the image and the multiple contour evolution. Therefore, the method is able to simultaneously extract multiple targets from the image. 3. By combining the image registration, statistical learning, and image segmentation, we perform a shape based method which not only utilizes the image information but also the shape knowledge. 4. A multi-scale shape representation based on the wavelet transformation is proposed. In particular, the shape is represented by wavelet coefficients in a hierarchical way in order to decompose the shape variance in multiple scales. Furthermore, the statistical shape learning and shape based segmentation is performed under such multi-scale shape representation framework.

The main objective of this dissertation is to apply Bayesian modeling to different complex and high-dimensional spatial data sets. I develop Bayesian hierarchical spatial models for both the observed location and the observation variable. Throughout this dissertation I execute the inference of the posterior distributions using Markov chain Monte Carlo by developing computational strategies that can reduce the computational cost. I start with a "high level" image analysis by modeling the pixels with a Gaussian process and the objects with a marked-point process. The proposed method is an automatic image segmentation and classification procedure which simultaneously detects the boundaries and classifies the objects in the image into one of the predetermined shape families. Next, I move my attention to the piecewise non-stationary Gaussian process models and their computational challenges for very large data sets. I simultaneously model the non-stationarity and reduce the computational cost by using the innovative technique of full-scale approximation. I successfully demonstrate the proposed reduction technique to the Total Ozone Matrix Spectrometer (TOMS) data. Furthermore, I extend the reduction method for the non-stationary Gaussian process models to a dynamic partition of the space by using a modified Treed Gaussian Model. This modification is based on the use of a non-stationary function and the full-scale approximation. The proposed model can deal with piecewise non-stationary geostatistical data with unknown partitions. Finally, I apply the method to the TOMS data to explore the non-stationary nature of the data.

Amphiphiles that possess a dual character, hydrophobic and hydrophilic, are employed in many chemical, pharmaceutical and biological applications. Amphiphile molecules that include a hydrophilic head and a hydrophobic tail can easily adsorb at a liquid/vapour interface, to reach to a minimum free energy and hence a most thermodynamically stable state. Surface tension is a key parameter for understanding such behavior of an amphiphile, or a surfactant. This thesis represents a comprehensive study on adsorption and surface tension of slightly volatile, organic amphiphiles in aqueous solution. Although for a vapor-liquid interface, adsorption from both liquid and vapor phases should be considered, they have been almost always considered exclusive of one another. When a volatile surfactant is dissolved in the liquid phase, it also applies a finite partial pressure in the vapor phase. Recently, dynamic surface tension experiments showed that adsorption from both sides of a vapor/liquid interface must be studied simultaneously. It is noted that surface tension phenomena are often dynamic, in particular when the surface under consideration is perturbed. With the newly discovered importance of adsorption from both sides of a vapor/liquid interface, one may have to ask the question: how dynamic surface tension is influenced and responding to the surface perturbation and environment changes, and whether both sides of the interface play a role in surface tension responses. In this research, axisymmetric drop shape analysis-profile (ADSA-P) is used for surface tension measurement. The experiments are performed in a closed chamber where the effects of surfactant concentrations of both liquid and vapor phases on the surface tension can be studied. The partial vapor pressure of surfactant is controlled with an environment solution containing the same surfactant as the sample solution. The environment solution is to facilitate adsorption from the vapor side of the interface by creating a surfactant vapor phase. The effects of surface perturbation, environment condition (i.e., temperature and pressure) and carbon chain length on the surface tension and adsorption kinetics are studied in detail. The surface tension response of 1-octanol aqueous solution to surface area perturbation is investigated. Upon surface compression, the surface tension decreases followed by a gradual increase back to the value prior to compression. On surface expansion, two categories of surface tension response are observed: First, when the change in surface area is smaller than 5%, the behavior similar to that of conventional surfactants is observed. The surface tension increases followed by a gradual decrease back to the value prior to expansion. Second, when the change in surface area is greater than 5%, and the drop concentration is sufficiently larger than the environment concentration, the surface tension initially slightly increases, but after a time delay, it sharply decreases, followed by a gradual increase back to the value prior to expansion. Previous studies showed that at steady-state condition a network of hydrogen bonding between surfactant and water molecules near the surface is created. The unique surface tension response after large expansion might be related to the momentarily destruction of this hydrogen bonding network and gradually making a new one. The effect of temperature on the surface tension and adsorption kinetics of 1-octanol, 1-hexanol and 1-butanol aqueous solutions is studied. The steady-state surface tension is found to decrease upon an increase in temperature, and a linear relationship is observed between them. The modified Langmuir equation of state and the modified kinetic transfer equation are used to model the experimental data of the steady-state and dynamic (time-dependent) surface tension, respectively. The equilibrium constants and adsorption rate constants are evaluated through a minimization procedure for temperatures ranging from 10°C to 35°C. From the steady-state modelling, the equilibrium constants for adsorption from vapor phase and liquid phase are found to increase with temperature. From the dynamic modelling, the adsorption rate constants for adsorption from vapor phase and liquid phase are found to increase with temperature too. The influence of carbon dioxide pressure on the surface tension and adsorption kinetics of the aforementioned surfactant aqueous solutions is investigated. To consider the effect of adsorption/desorption of the two species (surfactant and carbon dioxide) from both sides of a vapor/liquid interface on the surface tension, the modified Langmuir equation of state and the modified kinetic transfer equation are derived. The steady-state and dynamic surface tension data are modelled using the modified Langmuir equation of state and the modified kinetic transfer equation, respectively. The equilibrium constants and adsorption rate constants of surfactant and carbon dioxide are evaluated through a minimization procedure for CO2 pressures ranging from 0 to 690 KPa. From the steady-state modelling, the equilibrium parameters for surfactant and carbon dioxide adsorption from vapor phase and liquid phase are found unchanged for different pressures of carbon dioxide. From the dynamic modelling, the adsorption rate constants for surfactant and carbon dioxide are found to decrease with carbon dioxide pressure. The role of carbon chain length of amphiphiles in aqueous solution is also studied. It is illustrated that the equilibrium constants for adsorption from both sides of a vapor/liquid interface increase from 1-butanol to 1-octanol. The modelling results show that the ratio of the equilibrium constant for adsorption from vapor phase to the equilibrium constant for adsorption from liquid phase declines from 260 to 26 as the chain length is increased from 1-butanol to 1-octanol. Therefore, the contribution to adsorption from liquid phase augments as the chain length is increased. The adsorption kinetics for this group of short carbon chain surfactants is modelled using a kinetic transfer equation. The modelling results show that the adsorption rate constants from vapor phase and liquid phase (kag and kal) increase from 1-butanol to 1-octanol. Steady-state and dynamic modelling also reveals that the maximum surface concentration increases with carbon chain length. These results may be due to the higher hydrophobicity character of a surfactant molecule at longer carbon chain length.

Title: Correspondence Problem in Geometric Morphometrics Tasks Author: Václav Krajíček Department / Institute: Department of Software and Computer Science Education Supervisor of the doctoral thesis: RNDr. Josef Pelikán Supervisor's e-mail address: pepca@cgg.mff.cuni.cz Abstract: Shape analysis in physical anthropology, biomedicine, and related disci- plines is mostly done using landmarks or by measuring distances. New techno- logical advancements allow the digitization of object's appearance in the form of triangular meshes or volume images. These digital images are especially beneficial in the cases when landmarks cannot be used to effectively describe the shape. In order to statistically analyze shape in a sample of observations, which are represented by these modalities, correspondence has to be found. Registration is a crucial tool in mapping the shape representations into a common space where correspondence is found by nearest neighbor principle in the case of triangular meshes or by overlaps in the case of volume images. B- spline based non-rigid registration is chosen because of its versatility, relative speed and ability to handle both meshes and volume images. Experiments were also performed with other alternatives - Thin-plate splines and Coherent point drift. The algorithm was modified to handle...

Dans le cadre de la surveillance maritime, les opérationnels ont de plus en plus recours à l'imagerie radar pour classifier à grande distance un objet marin. Le traitement ISAR (Inverse Synthetic Aperture Radar) répond à ce besoin. Il repose en particulier sur l'analyse des mouvements propres de l'objet marin. Une fois l'objet détecté, il s'agit d'afficher sur la console tactique la représentation de la fréquence Doppler en fonction de la distance, aussi appelée image range-Doppler. Le travail présenté dans ce mémoire s'inscrit dans une perspective d'évolution opérationnelle de la chaîne de traitement existante. Il vise à produire de manière automatique la « meilleure » image range-Doppler. Dans cette thèse, nos contributions s'appuient sur l'idée de reconsidérer la chaîne de traitement en tenant compte de l'a priori que l'objet marin est un objet rigide dont la géométrie structure l'évolution du signal radar. Ainsi, dans une première contribution, nous proposons une nouvelle méthode d'analyse temps-fréquence du signal radar afin d'obtenir une image instantanée où l'opérationnel peut distinguer « au mieux » les superstructures de l'objet marin. Cette dernière est fondée sur la fusion de plusieurs représentations temps-fréquence issues de la classe de Cohen en faisant l'hypothèse que les composantes temps-fréquence sont des trajectoires structurées 2D dans le plan temps-fréquence, contrairement aux termes d'interférences induits par la propriété de bilinéarité des membres de cette classe. Une étude comparative sur données synthétiques et ISAR est menée pour confirmer la pertinence de notre approche, notamment du point de vue de la résolution temps-fréquence et de la suppression des termes d'interférences.Dans une seconde contribution, nous établissons une nouvelle procédure pour qualifier chaque image range-Doppler, obtenue à l'issue de l'analyse temps-fréquence, avec des mesures d'irrégularité de formes que nous fusionnons à l'aide d'un opérateur d'agrégation. Des simulations sur données réelles sont réalisées. Les résultats concordent avec une analyse subjective menée par des opérationnels, ce qui confirme l'efficacité de notre méthode. / In maritime surveillance, radar imaging plays a key role to classify a maritime object. ISAR processing is one of the solutions, which takes advantage of the object rotational motion to provide a range-Doppler image.The work, presented in this report, is an evolution of the existing ISAR processing chain. Therefore, our contributions are based on the processing chain reconsideration by taking into account the fact that the maritime object is a rigid object, the geometry of which influences the radar signal evolution.In a first contribution, we propose a new time-frequency analysis method based on the aggregation of some time-frequency representations obtained with Cohen class members. It consists in differentiating the signal, assumed to be characterized by 2-D near-linear stable trajectories in the time-frequency plane, and the cross-terms, assumed to be geometrically unstructured. A comparative study is then carried out on ISAR synthetic data to confirm the efficiency of our approach.In a second contribution, we present a new procedure to characterize each range-Doppler image, obtained from a time-frequency analysis, by means of shape irregularity measures that are combined with a fuzzy logic operator. To validate our approach, simulations on real data are done. The results are compared to a subjective analysis carried out with practionners.

Uma imagem engloba informação que precisa ser organizada para interpretar e compreender seu conteúdo. Existem diversas técnicas computacionais para extrair a principal informação de uma imagem e podem ser divididas em três áreas: análise de cor, textura e forma. Uma das principais delas é a análise de forma, por descrever características de objetos baseadas em seus pontos fronteira. Propomos um método de caracterização de imagens, por meio da análise de forma, baseada nas propriedades espectrais do laplaciano em grafos. O procedimento construiu grafos G baseados nos pontos fronteira do objeto, cujas conexões entre vértices são determinadas por limiares T_l. A partir dos grafos obtêm-se a matriz de adjacência A e a matriz de graus D, as quais definem a matriz Laplaciana L=D -A. A decomposição espectral da matriz Laplaciana (autovalores) é investigada para descrever características das imagens. Duas abordagens são consideradas: a) Análise do vetor característico baseado em limiares e a histogramas, considera dois parâmetros o intervalo de classes IC_l e o limiar T_l; b) Análise do vetor característico baseado em vários limiares para autovalores fixos; os quais representam o segundo e último autovalor da matriz L. As técnicas foram testada em três coleções de imagens: sintéticas (Genéricas), parasitas intestinais (SADPI) e folhas de plantas (CNShape), cada uma destas com suas próprias características e desafios. Na avaliação dos resultados, empregamos o modelo de classificação support vector machine (SVM), o qual avalia nossas abordagens, determinando o índice de separação das categorias. A primeira abordagem obteve um acerto de 90 % com a coleção de imagens Genéricas, 88 % na coleção SADPI, e 72 % na coleção CNShape. Na segunda abordagem, obtém-se uma taxa de acerto de 97 % com a coleção de imagens Genéricas; 83 % para SADPI e 86 % no CNShape. Os resultados mostram que a classificação de imagens a partir do espectro do Laplaciano, consegue categorizá-las satisfatoriamente. / An image includes information that needs to be organized to interpret and understand its contents. There are several computational techniques to extract the main information of images and are divided into three areas: color, texture and shape analysis. One of the main of them is shape analysis, since it describes objects getting main features based on reference points, usually border points. This dissertation proposes a shape analysis method based on the spectral properties of the Laplacian in graphs to represent images. The procedure builds G graphs based on object border points, whose connections between vertices are determined by thresholds T_l. From graphs G we obtain the adjacency matrix A and matrix degrees D, which define the Laplacian matrix L=D -A. Thus, spectral decomposition of the Laplacian matrix (eigenvalues) is investigated to describe image features. Two approaches are considered: a)Analysis of feature vector based on thresholds and histograms, it considers two parameters, classes range IC_l and threshold T_l; b) Analysis of feature vector based on multiple linear for fixed eigenvalues, which represents the second and final eigenvalue matrix L. The techniques were tested in three image datasets: synthetic (Generic), human intestinal parasites (SADPI) and plant leaves (CNShape), each of these with its own features and challenges. Afterwards to evaluate our results, we used the classification model Support Vector Machine (SVM) to evaluate our approaches, determining the percentage of separation of categories. The first approach achieved 90 % of precision with the Generic image dataset, 88 % in SADPI dataset, and 72 % in CNShape dataset. In the second approach, it obtains 97 % of precision with the Generic image dataset, 83 % for SADPI and 86 % in CNShape respectively. The results show that the classification of images from the Laplacian spectrum can categorize them satisfactorily.

A Dimensão Fractal pode ser utilizada para medir algumas características ligadas a complexidade da imagem, permitindo seu uso em análise de formas e texturas e reconhecimento de padrões. Neste trabalho é apresentado um estudo comparativo entre alguns dos principais métodos de estimativa da Dimensão Fractal. Foi realizada uma análise experimental e um estudo de casos para cada uma das técnicas, levando em consideração aspectos de implementação, precisão, variação de resultados segundo ajuste de parâmetros e tolerância a ruídos. Neste trabalho também foi desenvolvido um estudo sobre a Dimensão Fractal Multiescala, visando seu emprego como metodologia de assinatura de complexidade. Na literatura a técnica de multiescala é limitada ao método de Bouligand-Minkowski, sendo aqui ela estendida para outras metodologias de estimativa de Dimensão Fractal. Por meio de análise experimental as metodologias propostas foram comparadas e os resultados discutidos, enfatizando as vantagens e desvantagens destas técnicas. / Fractal Dimension can be used to measure some characteristics related to the image complexity, allowing its use on shape and texture analysis and pattern recognition. In this work is presented a comparative study among some of the most important methods to estimate Fractal Dimension. It was performed a experimental analysis and a case study for each one of the techniques, considering implementation aspects, precision, variation of results under parameters adjustments and noise tolerance. In this work is also performed a study about MultiScale Fractal Dimension, aiming at its use as a methodology of complexity signature. In the literature the multiscale technique is limited to Bouligand-Minkowski method, being here it extended to other methodologies of estimative of Fractal Dimension. By experimental analysis the proposed methodologies were compared and the results argued, emphasizing the advantages and disadvantages of those techniques.

Imagens codificadas por matrizes de intensidade são tipicamente representadas por grande quantidade de dados. Embora existam inúmeras abordagens para análise de imagens, o conhecimento sobre problemas específicos é raramente considerado. Este trabalho trata sobre problemas de análises de imagens cujas soluções dependem do conhecimento sobre os dados envolvidos na aplicação específica. Para isso, utiliza técnicas de mineração de dados para modelar as respostas humanas obtidas de experimentos psicofísicos. Dois problemas de análise de imagens são apresentados: (1) a análise de formas e (2) a análise pictórica. No primeiro problema (1), formas de neurônios da retina (neurônios ganglionares de gato) são segmentadas e seus contornos submetidos a uma calibração dos parâmetros de curvatura considerando a segmentação manual de um especialista. Outros descritores, tais como esqueletos multi-escalas são explorados para eventual uso e avaliação da abordagem. No segundo problema (2), a análise pictórica de imagens de home-pages serve para avaliar critérios estéticos a partir de medidas de complexidade, contraste e textura. O sistema generaliza as respostas por um experimento psicofísico realizados com humanos. Os resultados objetivos com as duas abordagens revelaram-se promissores, surpreendentes e com ampla aplicabilidade. / Images coded by intensity matrices typically involve large amount of data. Although image analysis approaches are diverse, knowledge about specific problems is rarely considered. This work is about image analysis problems whose solutions depend on the knowledge about the involved data. In order to do so data mining techniques are applied to model human response to psychophysical experiments. Two image analysis problems are addressed: (1) shape analysis; and (2) pictorial analysis. In the former, neuronal images (ganglion retinal cells of cat) are segmented and curvature parameters are calibrated to identify extremities and branches on the shape considering human segmentation as a reference. Descriptors such as multiscale skeletons are also explored for potential application or evaluations. In the second problem, a pictorial analysis of home-pages images feed an artificial aesthetics criteria evaluator based on complexity, contrast and texture features. The system models and generalizes the obtained human responses to psychophysical experiment. The results for these two approaches are promising, surprising and widely applicable.