Analyse de maillages surfaciques par construction et comparaison de modèles moyens et par décomposition par graphes s’appuyant sur les courbures discrètes : application à l’étude de la cornée humaine

Réalisé en cotutelle avec Aix Marseille Université.Cette thèse se découpe en trois parties. Les deux premières portent sur le développement de méthodes pour la construction de modèles géométriques moyens et pour la comparaison de modèles. Ces approches sont appliquées à la cornée humaine pour l’élaboration d’atlas et pour l’étude biométrique robuste. La troisième partie porte sur une méthode générique d'extraction d'informations dans un maillage en s'appuyant sur des propriétés différentielles discrètes afin de construire une structure par graphe permettant l'extraction de caractéristiques par une description sémantique. Les atlas anatomiques conventionnels (papier ou CD-ROM) sont limités par le fait qu'ils montrent généralement l'anatomie d'un seul individu qui ne représente pas nécessairement bien la population dont il est issu. Afin de remédier aux limitations des atlas conventionnels, nous proposons dans la première partie d’élaborer un atlas numérique 3D contenant les caractéristiques moyennes et les variabilités de la morphologie d'un organe, plus particulièrement de la cornée humaine. Plusieurs problématiques sont abordées, telles que la construction d'une cornée moyenne et la comparaison de cornées. Il existe à ce jour peu d'études ayant ces objectifs car la mise en correspondance de surfaces cornéennes est une problématique non triviale. En plus d'aider à développer une meilleure connaissance de l'anatomie cornéenne, la modélisation 3D de la cornée normale permet de détecter tout écart significatif par rapport à la "normale" permettant un diagnostic précoce de pathologies ou anomalies de la forme de la cornée. La seconde partie a pour objectif de développer une méthode pour reconnaître une surface parmi un groupe de surfaces à l’aide de leurs acquisitions 3D respectives, dans le cadre d’une application de biométrie sur la cornée. L’idée est de quantifier la différence entre chaque surface et une surface donnée, et de déterminer un seuil permettant la reconnaissance. Ce seuil est dépendant des variations normales au sein d’un même sujet, et du bruit inhérent à l’acquisition. Les surfaces sont rognées et trouées de façon imprévisible, de plus il n’y a pas de point de mise en correspondance commun aux surfaces. Deux méthodes complémentaires sont proposées. La première consiste à calculer le volume entre les surfaces après avoir effectué un recalage, et à utiliser ce volume comme un critère de similarité. La seconde approche s’appuie sur une décomposition en harmoniques sphériques en utilisant les coefficients comme des descripteurs de forme, qui permettront de comparer deux surfaces. Des résultats sont présentés pour chaque méthode en les comparant à la méthode la plus récemment décrite dans la littérature, les avantages et inconvénients de chacune sont détaillés. Une méthodologie en cascade utilisant ces deux méthodes afin de combiner les avantages de chacune est aussi proposée. La troisième et dernière partie porte sur une nouvelle méthode de décomposition en graphes de maillages 3D triangulés. Nous utilisons des cartes de courbures discrètes comme descripteur de forme afin de découper le maillage traité en huit différentes catégorie de carreaux (ou peak, ridge, saddle ridge, minimal, saddle valley, valley, pit et flat). Ensuite, un graphe d'adjacence est construit avec un nœud pour chaque carreau. Toutes les catégories de carreaux ne pouvant pas être adjacentes dans un contexte continu, des jonctions intermédiaires sont ajoutées afin d'assurer une cohérence continue entre les zones. Ces graphes sont utilisés pour extraire des caractéristiques géométriques décrites par des motifs (ou patterns), ce qui permet de détecter des régions spécifiques dans un modèle 3D, ou des motifs récurrents. Cette méthode de décomposition étant générique, elle peut être appliquée à de nombreux domaines où il est question d’analyser des modèles géométriques, en particulier dans le contexte de la cornée.This thesis comprises three parts. The first two parts concern the development of methods for the construction of mean geometric models and for model comparison. These approaches are applied to the human cornea for the construction of atlases and a robust biometric study. The third part focuses on a generic method for the extraction of information in a mesh. This approach is based on discrete differential properties for building a graph structure to extract features using a semantic description. Conventional anatomical atlases (paper or CD-ROM) are limited by the fact they generally show the anatomy of a single individual who does not necessarily represent the population from which they originate. To address the limitations of conventional atlases, we propose in the first part of this thesis to construct a 3D digital atlas containing the average characteristics and variability of the morphology of an organ, especially that of the human cornea. Several issues are addressed, such as the construction of an average cornea and the comparison of corneas. Currently, there are few studies with these objectives because the matching of corneal surfaces is a non-trivial problem. In addition to help to develop a better understanding of the corneal anatomy, 3D models of normal corneas can be used to detect any significant deviation from the norm, thereby allowing for an early diagnosis of diseases or abnormalities using the shape of the cornea. The second part of this thesis aims to develop a method for recognizing a surface from a group of surfaces using their 3D acquisitions in a biometric application pertinent to the cornea. The concept behind this method is to quantify the difference between each surface and a given surface and to determine the threshold for recognition. This threshold depends on normal variations within the same subject and noise due to the acquisition system. The surfaces are randomly trimmed and pierced ; moreover, there is no common landmark on the surfaces. Two complementary methods are proposed. The first method consists of the computation of the volume between the surfaces after performing geometrical matching and the use of this volume as a criterion of similarity. The second approach is based on a decomposition of the surfaces into spherical harmonics using the coefficients as shape descriptors to compare the two surfaces. Each result of the proposed methods is compared to the most recent method described in the literature, with the benefits and disadvantages of each one described in detail. A cascading methodology using both methods to combine the advantages of each method is also proposed. The third and final part of this thesis focuses on a new method for decomposing 3D triangulated meshes into graphs. We use discrete curvature maps as the shape descriptor to split the mesh in eight different categories (peak, ridge, saddle ridge, minimal, saddle valley, valley, pit and flat). Next, an adjacency graph is built with a node for each patch. Because all categories of patches cannot be adjacent in a continuous context, intermediate junctions are added to ensure the continuous consistency between patches. These graphs are used to extract geometric characteristics described by patterns that allow for the detection of specific regions in a 3D model or recurrent characteristics. This decomposition method, being generic, can be used in many applications to analyze geometric models, especially in the context of the cornea

Comparison of quasi-spherical surfaces : application to corneal biometry

In this study, the authors present two new techniques with their own particular advantages dedicated to the authentication of a person based on the three-dimensional geometry of the cornea. A device known as corneal topographer is used for capturing the shape of each cornea. Until now only a few studies on corneal biometry have been conducted and they were limited only to the anterior surface. In this study, since the whole cornea is a tissue layered by two (anterior and posterior) surfaces, the authors propose to use both surfaces to characterise the corneal shape. The first proposed method consists of comparing coefficients from a spherical harmonics decomposition, and this allows to do a fast comparison that can be used to perform many-to-one comparisons. The second approach is based on the minimal residual volume between two corneas after a registration step, this geometry-based method is more accurate but slower, and is thus used to perform one-to-one comparisons. A cascade fusion scheme is also proposed to benefit from the advantages of both methods. The authors’ study demonstrates that corneal shape could be used for biometry. The two proposed methods have been tested and validated on a dataset of 257 corneas

Automatic CAD Assemblies Generation by Linkage Graph Overlay for Machine Learning Applications

This paper introduces an approach to synthetize new CAD assemblies from existing STEP files. The algorithm first generates linkage graph by detecting linkage between components. Then it detects linkages similarities between components of different assemblies while analyzing the associated graphs. Finally, it exchanges the similar components. The similarities in a family of components must be formalized by the user. Then the similar components can be replaced by the other through smart placements. This method allows to automatically generate a wide variety of new consistent assemblies sharing the same semantics, in order to create databases of CAD assemblies ready for machine learning applications. It has been validated on several cases

SMA-Net: Deep learning-based identification and fitting of CAD models from point clouds

Identifcation and ftting is an important task in reverse engineering and virtual/augmented reality. Compared to the traditional approaches, carrying out such tasks with a deep learning-based method have much room to exploit. This paper presents SMA-Net (Spatial Merge Attention Network), a novel deep learning-based end-to-end bottom-up architecture, specifcally focused on fast identifcation and ftting of CAD models from point clouds. The network is composed of three parts whose strengths are clearly highlighted: voxel-based multi-resolution feature extractor, spatial merge attention mechanism and multi-task head. It is trained with both virtually-generated point clouds and as-scanned ones created from multiple instances of CAD models, themselves obtained with randomly generated parameter values. Using this data generation pipeline, the proposed approach is validated on two diferent data sets that have been made publicly available: robot data set for Industry 4.0 applications, and furniture data set for virtual/augmented reality. Experiments show that this reconstruction strategy achieves compelling and accurate results in a very high speed, and that it is very robust on real data obtained for instance by laser scanner and Kinect

As-scanned point clouds generation for virtual Reverse Engineering of CAD assembly models

This paper introduces a new approach for the generation of as-scanned point clouds of CAD assembly models. The resulting point clouds incorporate various realistic artifacts that would appear if the corresponding real objects were digitalized with a laser scanner. Such a virtual Reverse Engineering technique can produce a huge amount of realistic point clouds much faster than using classical time-consuming Reverse Engineering techniques on real physical objects. Here, there is no need to use a laser scanner and the post-processing steps are automatic. Using this technique, it is easy to create large databases of point clouds automatically segmented and labeled from the CAD models and which can be used for supervised machine learning. The proposed approach starts by generating a triangle mesh wrapping the CAD assembly model to be reverse engineered. The resulting watertight mesh is then sampled to obtain a more realistic distribution of points. The occlusion phenomenon is then simulated using a hidden point removal algorithm launched from several viewpoints. A misalignment procedure can optionally be used to simulate the fact that in real-life Reverse Engineering the position and orientation of the laser scanner and/or real object would have been changed to get a different scanning viewpoint. The virtual Reverse Engineering process ends by generating noise and by inserting outliers. The approach is illustrated and validated on several industrial examples

On the Use of Quality Metrics to Characterize Structured Light-based Point Cloud Acquisitions

Even if 3D acquisition systems are nowadays more and more efficient, the resulting point clouds nevertheless contain quality defects that must be taken into account beforehand, in order to better anticipate and control their effects. Assessing the quality of 3D acquisitions has therefore become a major issue for scan planning. This paper presents several quality metrics that are then studied to identify those that could be used to optimize the acquisition positions to perform an automatic scan. From the experiments, it appears that, when considering multiple acquisition positions, the coverage ratio and score indicator have significant changes and can be used to evaluate the quality of the measurements. Differently, other indicators such as efficacy ratio, registration error and metrological characteristics are insensitive to some acquisition position

User-Driven Computer-Assisted Reverse Engineering of Editable CAD Assembly Models

This paper introduces a novel reverse engineering (RE) technique for the reconstruction of editable computer-aided design (CAD) models of mechanical parts’ assemblies. The input is a point cloud of a mechanical parts’ assembly that has been acquired as a whole, i.e., without disassembling it prior to its digitization. The proposed framework allows for the reconstruction of the parametric CAD assembly model through a multi-step reconstruction and fitting approach. It is modular and it supports various exploitation scenarios depending on the available data and starting point. It also handles incomplete datasets. The reconstruction process starts from roughly sketched and parameterized CAD geometries (i.e., 2D sketches, 3D parts, or assemblies) that are then used as input of a simulated annealing-based fitting algorithm, which minimizes the deviation between the point cloud and the adapted geometries. The coherence of the CAD models is maintained by a CAD modeler that performs the geometries’ updates while guaranteeing the possibly imposed constraints and model coherence. The optimization process leverages a two-level filtering technique able to capture and manage the boundaries of the geometries inside the overall point cloud in order to allow local fitting and interfaces detection. It is a user-driven approach where the user decides what are the most suitable steps and sequence to operate. It has been tested and validated on both real scanned point clouds and as-scanned virtually generated point clouds incorporating several artifacts that would appear with real acquisition devices

Simulated annealing-based fitting of CAD models to point clouds of mechanical parts’ assemblies

This paper introduces a new ftting approach to allow an efcient part-by-part reconstruction or update of editable CAD models fitting the point cloud of a digitized mechanical parts′ assembly. The idea is to make use of parameterized CAD mod els whose dimensional parameters are to be optimized to match the acquired point cloud. Parameters may also be related to assembly constraints, e.g. the distance between two parts. The optimization kernel relies on a simulated annealing algorithm to fnd out the best values of the parameters so as to minimize the deviations between the point cloud and the CAD models to be ftted. Both global and local ftting are possible. During the optimization process, the orientation and positioning of the CAD parts are driven by an ICP algorithm. The modifcations are ensured by the batch calls to a CAD modeler which updates the models as the ftting process goes on. The modeler also handles the assembly constraints. Both single and multiple parts can be ftted, either sequentially or simultaneously. The evaluation of the proposed approach is performed using both real scanned point clouds and as-scanned virtually generated point clouds which incorporate several artifacts that could appear with a real scanner. Results cover several Industry 4.0 related application scenarios, ranging from the global ftting of a single part to the update of a complete Digital Mock-Up embedding assembly constraints. The proposed approach demonstrates good capacities to help maintaining the coherence between a product/system and its digital twi

Case‑based tuning of a metaheuristic algorithm exploiting sensitivity analysis and design of experiments for reverse engineering applications

Due to its capacity to evolve in a large solution space, the Simulated Annealing (SA) algorithm has shown very promising results for the Reverse Engineering of editable CAD geometries including parametric 2D sketches, 3D CAD parts and assem blies. However, parameter setting is a key factor for its performance, but it is also awkward work. This paper addresses the way a SA-based Reverse Engineering technique can be enhanced by identifying its optimal default setting parameters for the ftting of CAD geometries to point clouds of digitized parts. The method integrates a sensitivity analysis to characterize the impact of the variations in the parameters of a CAD model on the evolution of the deviation between the CAD model itself and the point cloud to be ftted. The principles underpinning the adopted ftting algorithm are briefy recalled. A framework that uses design of experiments (DOEs) is introduced to identify and save in a database the best setting parameter values for given CAD models. This database is then exploited when considering the ftting of a new CAD model. Using similar ity assessment, it is then possible to reuse the best setting parameter values of the most similar CAD model found in the database. The applied sensitivity analysis is described together with the comparison of the resulting sensitivity evolution curves with the changes in the CAD model parameters imposed by the SA algorithm. Possible improvements suggested by the analysis are implemented to enhance the efciency of SA-based ftting. The overall approach is illustrated on the ftting of single mechanical parts but it can be directly extended to the ftting of parts’ assemblies. It is particularly interesting in the context of the Industry 4.0 to update and maintain the coherence of the digital twins with respect to the evolution of the associated physical products and systems

ZO-1 Intracellular Localization Organizes Immune Response in Non-Small Cell Lung Cancer

International audienceDelocalization of zonula occludens-1 (ZO-1) from tight junctions plays a substantial role in epithelial cell plasticity observed during tumor progression. In vitro , we reported an impact of ZO-1 cyto-nuclear content in modulating the secretion of several pro-inflammatory chemokines. In vivo , we demonstrated that it promotes the recruitment of immune cells in mouse ear sponge assays. Examining lung cancers, we showed that a high density of CD8 cytotoxic T cells and Foxp3 immunosuppressive regulatory T cells in the tumor microenvironment correlated with a cyto-nuclear expression of ZO-1. Taken together, our results support that, by affecting tumor cell secretome, the cyto-nuclear ZO-1 pool may recruit immune cells, which could be permissive for tumor progression