During vertebrate embryo development, the body axis is subdivided into repeated structures, called somites. Somites bud off from an un-segmented tissue called the pre-somitic mesoderm (PSM) in a sequential and periodic manner, tightly controlled by an in built molecular clock, called the "segmentation clock". According to current understanding, the clock is comprised of: (i) an autonomous cellular oscillator consisting of an intracellular negative feedback loop of Her genes within the PSM cells, (ii) Delta-ligand and Notch-receptor coupling that facilitates synchronization of oscillators among the PSM cells, (iii) Tissue level waves of gene expression that emerge in the posterior PSM and move coherently towards anterior, leading to global arrest of oscillations in the form of somites. However, the movement of cellular oscillators within the PSM before the formation of somitic furrows, a prominent feature of the tissue as observed through this work has not been experimentally considered as a constituent of the segmentation clock so far. Our work aims to incorporate movement of cellular oscillators in the framework of the segmentation clock. It is well known from theoretical studies that the characteristics of relative motion of oscillators affect their synchronization properties and the patterns of oscillations they form. Particularly, theoretical studies by Uriu et al., PNAS (2010) suggest that cell movements promotes synchronization of genetic oscillations. Here, we established experimental techniques and image analysis tools to attain quantitative insight on (i) diffusion co-efficient of cellular oscillators, (ii) dynamics of a population of oscillators, within the PSM aiming towards concomitant understanding of the relationship between movement and synchronization of cellular oscillators. In order to quantitatively relate cellular oscillators and their motion within the PSM, I established imaging techniques that enabled visualization of fluorescenctly labeled nuclei as readouts of cell positions in live embryo, and developed dedicated segmentation algorithm and implemented tracking protocol to obtain nuclei positions over time in 3D space. Furthermore, I provide benchmarking techniques in the form of artificial data that validate segmentation algorithm efficacy and, for the first time proposed the use of transgenic embryo chimeras to validate segmentation algorithm performance within the context of in vivo live imaging of embryonic tissues. Preliminary analysis of our data suggests that there is relatively high cell mixing in the posterior PSM, within the same spatial zone where synchronous oscillations emerge at maximum speed. Also, there are indications of gradient of cell mixing along the anterior-posterior axis of the embryo. By sampling single cell tracks with the help of nuclei markers, we have also been able to follow in vivo protein oscillations at single cell resolution that would allow quantitative characterization of coherence among a population of cellular oscillators over time. Our image analysis work flow allows testing of mutant embryos and perturbation of synchrony dynamics to understand the cause-effect relationship between movement and synchronization properties at cellular resolution. Essentially, through this work, we hope to bridge the time scales of events and cellular level dynamics that leads to highly coordinated tissue level patterns and thereby further our understanding of the segmentation clock mechanism.

Technologies in image acquisition have developed and often provide image volumes in more than two dimensions. Computer tomography and magnet resonance imaging provide image volumes in three spatial dimensions. The image enhancement methods have developed as well and in this thesis work 3D image enhancement with filter networks is evaluated. The aims of this work are; to find a method which makes the initial parameter settings in the 3D image enhancement processing easier, to compare 2D and 3D processed image volumes visualized with different visualization techniques and to give an illustration of the benefits with 3D image enhancement processing visualized using these techniques. The results of this work are; 1. a parameter setting tool that makes the initial parameter setting much easier and 2. an evaluation of 3D image enhancement with filter networks that shows a significant enhanced image quality in 3D processed image volumes with a high noise level compared to the 2D processed volumes. These results are shown in slices, MIP and volume rendering. The differences are even more pronounced if the volume is presented in a different projection than the volume is 2D processed in.

Dans ce travail nous nous intéressons à la segmentation d’image 3D. Le but est de définir un cadre permettant, étant donnée une problématique de segmentation, de développer rapidement un algorithme apportant une solution à cette problématique. Afin de ne pas être restreint à un sous ensemble des types de problématique de segmentation, ce cadre doit permettre de mettre en oeuvre efficacement les différentes méthodes et les différents critères de segmentation existants, dans le but de les combiner pour définir les nouveaux algorithmes. Ce cadre doit reposer sur un modèle de structuration d’image qui représente la topologie et la géométrie d’une partition et permet d’en extraire efficacement les informations requises. Dans ce document, les différentes méthodes de segmentation existantes sont présentées afin de définir un ensemble d’opération nécessaire à leur implémentation. Une présentation des modèles existants est faite pour en déterminer avantages et inconvénients, puis le nouveau modèle est ensuite défini. Sa mise en oeuvre complète est détaillée ainsi qu’une analyse de sa complexité en temps et en mémoire pour l’ensemble des opérations précédemment définies. Des exemples d’utilisation du modèle sur des cas concrets sont ensuite décrits, ainsi que les possibilités d’extension du modèle et d’implémentation sur architecture parallèle. / In this work we focus on 3D image segmentation. The aim consists in defining a framework which, given a segmentation problem, allows to design efficiently an algorithm solving this problem. Since this framework has to be unspecific according to the kind of segmentation problem, it has to allow an efficient implementation of most segmentation techniques and criteria, in order to combine them to define new algorithms. This framework has to rely on a structuring model both representing the topology and the geometry of the partition of an image, in order to efficiently extract required information. In this document, different segmentation techniques are presented in order to define a set of primitives required for their implementation. Existing models are presented with their advantages and drawbacks, then the new structuring model is defined. Its whole implementation including details of its memory consumption and time complexity for each primitives of the previously defined set of requirements is given. Some examples of use with real image analysis problems are described, with also possible extensions of the model and its implementation on parallel architecture.

L’imagerie médicale joue un rôle de plus en plus important avec le développement de nombreuses techniques d’acquisition. Il faut principalement pouvoir restaurer (débruiter) les images et en faire une segmentation. Ainsi toute l’information qualitative et quantitative sera disponible pour affiner les diagnostics. Dans cette thèse nous proposons une contribution à cette analyse dans un contexte 3D. Nous étudions deux grands types de méthodes : les méthodes variationnelles et les méthodes par ondelettes. Nous commençons par présenter les modèles variationnels du second ordre, qui s’avèrent plus performants que la classique méthode du premier ordre de Rudin-Osher-Fatemi. Nous l’utilisons pour débruiter et segmenter après avoir donné un bref état de l’art des procédés d’acquisition des images en médecine. Nous introduisons ensuite la transformée en ondelettes et présentons des algorithmes basés sur cette méthode. Les résultats numériques montrent que ces méthodes sont performantes et compétitives. Le coeur de notre travail est de développer des rerésentations 3D qui sont bien adaptées à des données médicales complexes comme des images IRM sous échantillonnées, peu contrastées (cervelets de souris) ou des images IRM d’angiographie (cerveaux de souris). Chaque technique a ses avantages et ses inconvénients. Aussi nous proposons un modèle variationnel mixte second ordre / seuillage par ondelettes. Ce modèle se comporte particulièrement bien : le bruit est correctement éliminé et les contours et textures préservés. Pour finir, nous adaptons plusieurs méthodes de fermeture de contours (hystérésis et distance de chanfrein) dans un contexte 3D. Le mémoire se termine par une synthèses des résultats et une présentation de futures directions de recherche. / Medical procedures have become a critical application area that makes substantial use of image processing. Medical image processing tasks mainly deal with image restoration, image segmentation that bring out medical image details, measure quantitatively medical conditions etc. The diagnosis of a health problem is now highly dependent on the quality and the credibility of the image analysis. The practical contributions of this thesis can be considered in many directions for medical domain. This manuscript addresses a 3D image analysis with variational methods and wavelet transform in the context of medical image processing. We first survey the second-order variational minimization model, which was proved that better than the classical Rudin-Osher-Fatemi model. This method is considered in problems associated to image denoising, image segmentation, that makes a short state of the art on medical imaging processing techniques. Then we introduce the concept of wavelet transform and present some algorithms that also used in this domain. Experimental results show that these tools are very useful and competitive. The core of this research is the development of new 3D representations, which are well adapted to representing complicated medical data, and filament structures in 3D volumes: the cerebellum and mice vessels network. Each of these two based methods has advantages and disadvantages, we then propose a new modified model that combines these schemes in the rest of the thesis. In this situation we propose a new modified model that combines these schemes. With the new decomposition model, in the reconstructed image, noise can be removed successfully and contours, textures are well preserved. This leads to further improvements in denoising performance. Finally, the further part of the thesis is devoted to the description of contribution to extend some classical contour closing methods, namely hysteresis thresholding and contour closing based on chamfer distance transform, in the 3D context. The thesis concludes with a review of our main results and with a discussion of a few of many open problems and promising directions for further research and application.

A formação de arcos – estruturas que promovem a anisotropia de forças dentro de um sistema – acontece corriqueiramente dentro de silos ou maquinaria agrícola. A presente tese propõe um modelo baseado em redes complexas para modelar tal fenômeno, definindo cada grão como vértice e a força que dois grãos trocam como o peso de uma ligação entre eles. A partir de ensaios tomográficos de 11 diferentes tipos de grãos foi desenvolvido um método para transformar cada uma das imagens tridimensionais resultantes numa rede complexa. Cada imagem foi pré-processada e submetida a uma transformada watershed utilizando como marcadores internos a erosão da própria imagem. Este processo tridimensional resultou na segmentação de cada um dos grãos da imagem original, tornando possível a extração de propriedades físicas de cada grão, como massa, centro de massa, momento de inércia, e as forças às quais este está submetido. A partir destes dados, a rede complexa de cada uma das 11 amostras foi construída. A amostra da soja foi comparada com um padrão-ouro pré-estabelecido possibilitando eventuais refinos no método. As reconstruções tridimensionais segmentadas de cada amostra apresentaram um resultado visual aceitável, embora algumas segmentações tenham sofrido com o efeito do elemento estruturante da erosão, uma vez que este tem de ser grande o suficiente para segmentar grãos adjacentes, porém não o suficiente para super-segmentar um único grão. A rede complexa formada a partir da imagem de soja foi submetida a uma análise mais profunda, estudando e normalizando sua propriedade strength, uma natural candidata para detectar anisotropia de forças. Os vértices com alto valor normalizado de strength foram definidos como o arco da estrutura, e sua análise visual permitiu concluir que estes de fato são os elementos responsáveis pela estrutura do arranjo, assim como substanciar o sucesso do método aqui proposto em detectar automaticamente o arco utilizando uma imagem tridimensional. / The formation of arches – structures that promotes force anisotropy within a system – appears routinely inside silos or agricultural machinery. This current thesis proposes a method for modeling this phenomenon as a complex network, defining each grain as vertex and a force that two grains exchanges as the weight of the link between them. By using computed tomography, 3D images were taken from 11 grain samples, and a method developed to transform each of this resulting images in a complex network. Each image had to be pre-processed and subjected to a watershed transform using as inner markers the erosion of the image itself. This process resulted in three-dimensional segmentation of each grain of the original image, allowing the estimation of the physical properties of each grain, such as mass, center of mass, moment of inertia and the forces to which the grain is subjected. From these measures, the complex network of each of the 11 samples was constructed. Sample soybeans were compared with a gold-standard, allowing improvements to the methodology. The segmented three-dimensional reconstructions of each sample provided acceptable visual output, although some samples suffered from erosion due to the structural element size, since it must be large enough to segment adjacent grains, but not enough to super-segment a single grain. The complex network obtained from the soybeans image was subjected to further analysis, studying and normalizing its strength property, a natural candidate to detect force anisotropy. Vertices with high normalized values of strength were understood as defining the arch of the structure, and its visual analysis showed that these indeed are the elements responsible for the arrangement structure. These results support the ability of the proposed method in automatically detecting the arches using as input a three-dimensional image.

Holoscopic 3D imaging “Integral imaging” was first proposed by Lippmann in 1908. It has become an attractive technique for creating full colour 3D scene that exists in space. It promotes a single camera aperture for recording spatial information of a real scene and it uses a regularly spaced microlens arrays to simulate the principle of Fly’s eye technique, which creates physical duplicates of light field “true 3D-imaging technique”. While stereoscopic and multiview 3D imaging systems which simulate human eye technique are widely available in the commercial market, holoscopic 3D imaging technology is still in the research phase. The aim of this research is to investigate spatial resolution of holoscopic 3D imaging and display technology, which includes holoscopic 3D camera, processing and display. Smart microlens array architecture is proposed that doubles spatial resolution of holoscopic 3D camera horizontally by trading horizontal and vertical resolutions. In particular, it overcomes unbalanced pixel aspect ratio of unidirectional holoscopic 3D images. In addition, omnidirectional holoscopic 3D computer graphics rendering techniques are proposed that simplify the rendering complexity and facilitate holoscopic 3D content generation. Holoscopic 3D image stitching algorithm is proposed that widens overall viewing angle of holoscopic 3D camera aperture and pre-processing of holoscopic 3D image filters are proposed for spatial data alignment and 3D image data processing. In addition, Dynamic hyperlinker tool is developed that offers interactive holoscopic 3D video content search-ability and browse-ability. Novel pixel mapping techniques are proposed that improves spatial resolution and visual definition in space. For instance, 4D-DSPM enhances 3D pixels per inch from 44 3D-PPIs to 176 3D-PPIs horizontally and achieves spatial resolution of 1365 × 384 3D-Pixels whereas the traditional spatial resolution is 341 × 1536 3D-Pixels. In addition distributed pixel mapping is proposed that improves quality of holoscopic 3D scene in space by creating RGB-colour channel elemental images.

abstract: Energy return in footwear is associated with the damping behavior of midsole foams, which stems from the combination of cellular structure and polymeric material behavior. Recently, traditional ethyl vinyl acetate (EVA) foams have been replaced by BOOST(TM) foams, thereby reducing the energetic cost of running. These are bead foams made from expanded thermoplastic polyurethane (eTPU), which have a multi-scale structure consisting of fused porous beads, at the meso-scale, and thousands of small closed cells within the beads at the micro-scale. Existing predictive models coarsely describe the macroscopic behavior but do not take into account strain localizations and microstructural heterogeneities. Thus, enhancement in material performance and optimization requires a comprehensive understanding of the foam’s cellular structure at all length scales and its influence on mechanical response. This dissertation focused on characterization and deformation behavior of eTPU bead foams with a unique graded cell structure at the micro and meso-scale. The evolution of the foam structure during compression was studied using a combination of in situ lab scale and synchrotron x-ray tomography using a four-dimensional (4D, deformation + time) approach. A digital volume correlation (DVC) method was developed to elucidate the role of cell structure on local deformation mechanisms. The overall mechanical response was also studied ex situ to probe the effect of cell size distribution on the force-deflection behavior. The radial variation in porosity and ligament thickness profoundly influenced the global mechanical behavior. The correlation of changes in void size and shape helped in identifying potentially weak regions in the microstructure. Strain maps showed the initiation of failure in cell structure and it was found to be influenced by the heterogeneities around the immediate neighbors in a cluster of voids. Poisson’s ratio evaluated from DVC was related to the microstructure of the bead foams. The 4D approach taken here provided an in depth and mechanistic understanding of the material behavior, both at the bead and plate levels, that will be invaluable in designing the next generation of high-performance footwear. / Dissertation/Thesis / Doctoral Dissertation Materials Science and Engineering 2020

Content: The intrinsic structure significantly influences the mechanical properties of leather. In consequence, knowledge of leather’s hierarchical structure is essential in order to find the most suited leather for specific application. Leather structure based parameters are of major importance for both manufacturing and leather processing industries. In this respect, intensive structure investigations have been subjected in continuous research work. Quantitative image analysis combined with stochastic micro-structure modelling and numerical simulation of macroscopic properties is a promising approach to gain a deeper understanding of complex relations between material’s micro-structure geometry and macroscopic properties. Key ingredient is a reliable geometric description provided by the quantitative analysis of 3D images of the material micro-structures. For leather, both imaging and image analysis are particularly challenging, due to the multi-scale nature of the leather’s micro-structure. Scales in leather are not well separated. Previously, high resolution computed tomography allowed 3D imaging of purely vegetable tanned leather samples at micro- and submicro- scale. Segmentation of leather structure as well as of typical structural elements in resulting image data is however hampered by a strong heterogeneity caused by lower scale structural information. The first method for automatic segmentation of typical structural elements at varying scales combined morphological smoothing with defining and iteratively coarsening regions using the waterfall algorithm on local orientations. It yields a hierarchical segmentation of the leather into coarse and fine structural elements that can be used to analyze and compare the structure of leather samples. Size and shape of the structural elements as well as their sub-structure yield information, e. g. on undulation, branching, thickness, cross-sectional shape, and preferred directions. In order to compare the micro-structure of leather samples from various body parts or even species, the segmentation has to be applicable without extensive pre-processing and parameter tuning. Robustness can be gained by applying smoothing methods that are adapted to the goal of defining image regions by similar local orientation. The challenge is that the space of fiber orientations in 3D is not equipped with an order. Motivated by a recent approach for nevertheless defining erosion and dilation on the sphere, we suggest new definitions for these morphological base transformations on the space of directions in 3D. We present segmentation results for 3D images of leather samples derived by these new morphological smoothing methods. Take-Away: The intrinsic structure significantly influences the mechanical properties of leather. Leather’s hierarchical structure can be analyzed by quantitative 3D image analysis combined with stochastic micro-structure modelling. Segmentation results for 3D images of leather samples derived by new morphological smoothing methods.

Master´s thesis is describing basic concepts in machine vision. Used camera systems and possible imaging 2D and 3D are described. Practical part deals with constructin of scanning device with linear actuator, conveyor belt, camera and laser. For experimental use is construction of scanning device made for 2D and 3D image using several methods.

This thesis deals with the possibilities of 3D vision. The theoretical part describes the principles of machine vision, constitutes the basic elements, description and the methods of measurement and 3D. The practical part is focused on the design of experimental workplace, which is consists of conveyor, experimental stand, industrial robot and PLC control. The system used to recognize and grasp objects undirected. Construction chapter focuses on the treatment needs of the conveyor for sensing applications and design of experimental stand with linear axis, which is equipped with camera and lasers. Furthermore solved by a communication network between the elements of work includes the design of their communications with the description of the control of its individual elements.