Relevant bibliographies by topics / Statistical shape modeling

Academic literature on the topic 'Statistical shape modeling'

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Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Statistical shape modeling"

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Choi, Myung Hwan, Bon Yeol Koo, Je Wook Chae, and Jay Jung Kim. "Parametric Shape Modeling of Femurs Using Statistical Shape Analysis." Transactions of the Korean Society of Mechanical Engineers A 38, no. 10 (October 1, 2014): 1139–45. http://dx.doi.org/10.3795/ksme-a.2014.38.10.1139.

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Huang, Yichen, Dale L. Robinson, Jonathan Pitocchi, Peter Vee Sin Lee, and David C. Ackland. "Glenohumeral joint reconstruction using statistical shape modeling." Biomechanics and Modeling in Mechanobiology 21, no. 1 (November 27, 2021): 249–59. http://dx.doi.org/10.1007/s10237-021-01533-6.

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Dai, Hang, Nick Pears, William Smith, and Christian Duncan. "Statistical Modeling of Craniofacial Shape and Texture." International Journal of Computer Vision 128, no. 2 (November 9, 2019): 547–71. http://dx.doi.org/10.1007/s11263-019-01260-7.

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Abstract We present a fully-automatic statistical 3D shape modeling approach and apply it to a large dataset of 3D images, the Headspace dataset, thus generating the first public shape-and-texture 3D morphable model (3DMM) of the full human head. Our approach is the first to employ a template that adapts to the dataset subject before dense morphing. This is fully automatic and achieved using 2D facial landmarking, projection to 3D shape, and mesh editing. In dense template morphing, we improve on the well-known Coherent Point Drift algorithm, by incorporating iterative data-sampling and alignment. Our evaluations demonstrate that our method has better performance in correspondence accuracy and modeling ability when compared with other competing algorithms. We propose a texture map refinement scheme to build high quality texture maps and texture model. We present several applications that include the first clinical use of craniofacial 3DMMs in the assessment of different types of surgical intervention applied to a craniosynostosis patient group.
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Harris, Michael D., Manasi Datar, Ross T. Whitaker, Elizabeth R. Jurrus, Christopher L. Peters, and Andrew E. Anderson. "Statistical shape modeling of cam femoroacetabular impingement." Journal of Orthopaedic Research 31, no. 10 (July 7, 2013): 1620–26. http://dx.doi.org/10.1002/jor.22389.

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Smelkina, N. A., R. N. Kosarev, A. V. Nikonorov, I. M. Bairikov, K. N. Ryabov, A. V. Avdeev, and N. L. Kazanskiy. "RECONSTRUCTION OF ANATOMICAL STRUCTURES USING STATISTICAL SHAPE MODELING." Computer Optics 41, no. 6 (January 1, 2017): 897–904. http://dx.doi.org/10.18287/2412-6179-2017-41-6-897-904.

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Wang, Xiaokan. "Statistical shape analysis for face movement manifold modeling." Optical Engineering 51, no. 3 (March 29, 2012): 037004. http://dx.doi.org/10.1117/1.oe.51.3.037004.

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Pishchulin, Leonid, Stefanie Wuhrer, Thomas Helten, Christian Theobalt, and Bernt Schiele. "Building statistical shape spaces for 3D human modeling." Pattern Recognition 67 (July 2017): 276–86. http://dx.doi.org/10.1016/j.patcog.2017.02.018.

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Hierl, Thomas, Hans-Martin Doerfler, Heike Huempfner-Hierl, and Daniel Kruber. "Evaluation of the Midface by Statistical Shape Modeling." Journal of Oral and Maxillofacial Surgery 79, no. 1 (January 2021): 202.e1–202.e6. http://dx.doi.org/10.1016/j.joms.2020.08.034.

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Mendoza, Carlos S., Nabile Safdar, Kazunori Okada, Emmarie Myers, Gary F. Rogers, and Marius George Linguraru. "Personalized assessment of craniosynostosis via statistical shape modeling." Medical Image Analysis 18, no. 4 (May 2014): 635–46. http://dx.doi.org/10.1016/j.media.2014.02.008.

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Ramachandran, Srinivas, Feng Ding, Kevin M. Weeks, and Nikolay V. Dokholyan. "Statistical Analysis of SHAPE-Directed RNA Secondary Structure Modeling." Biochemistry 52, no. 4 (January 14, 2013): 596–99. http://dx.doi.org/10.1021/bi300756s.

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Dissertations / Theses on the topic "Statistical shape modeling"

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Besbes, Ahmed. "Image segmentation using MRFs and statistical shape modeling." Phd thesis, Ecole Centrale Paris, 2010. http://tel.archives-ouvertes.fr/tel-00594246.

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Nous présentons dans cette thèse un nouveau modèle statistique de forme et l'utilisons pour la segmentation d'images avec a priori. Ce modèle est représenté par un champ de Markov. Les noeuds du graphe correspondent aux points de contrôle situés sur le contour de la forme géométrique, et les arêtes du graphe représentent les dépendances entre les points de contrôle. La structure du champ de Markov est déterminée à partir d'un ensemble de formes, en utilisant des techniques d'apprentissage de variétés et de groupement non-supervisé. Les contraintes entre les points sont assurées par l'estimation des fonctions de densité de probabilité des longueurs de cordes normalisées. Dans une deuxième étape, nous construisons un algorithme de segmentation qui intègre le modèle statistique de forme, et qui le relie à l'image grâce à un terme région, à travers l'utilisation de diagrammes de Voronoi. Dans cette approche, un contour de forme déformable évolue vers l'objet à segmenter. Nous formulons aussi un algorithme de segmentation basé sur des détecteurs de points d'intérêt, où le terme de régularisation est lié à l'apriori de forme. Dans ce cas, on cherche à faire correspondre le modèle aux meilleurs points candidats extraits de l'image par le détecteur. L'optimisation pour les deux algorithmes est faite en utilisant des méthodes récentes et efficaces. Nous validons notre approche à travers plusieurs jeux de données en 2D et en 3D, pour des applications de vision par ordinateur ainsi que l'analyse d'images médicales.
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Lamecker, Hans. "Variational and statistical shape modeling for 3D geometry reconstruction." München Verl. Dr. Hut, 2008. http://d-nb.info/992163226/04.

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Lamecker, Hans [Verfasser]. "Variational and statistical shape modeling for 3D geometry reconstruction / Hans Lamecker." Berlin : Freie Universität Berlin, 2008. http://d-nb.info/1023329603/34.

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Salhi, Asma. "Towards a combined statistical shape and musculoskeletal modeling framework for pediatric shoulder joint." Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2019. http://www.theses.fr/2019IMTA0137/document.

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La paralysie obstétricale du plexus brachial (POPB) est une paralysie du membre supérieur qui survient à la naissance et peut entraîner une déformation de l'articulation et un fonctionnement anormal de l'épaule. Bien que le traitement de la POPB tente de restaurer la fonction de l'épaule, la pathomécanique sous-jacente n'est pas encore clairement comprise. Les modèles computationnels sont efficaces pour fournir de telles informations, mais il n'existe aucun modèle d'articulation de l'épaule pédiatrique pour comprendre la POPB. Ainsi, ce travail de recherche a pour but de construire un framework combinant les avancées dans les domaines de la modélisation statistique de forme (MSF) et de la modélisation musculo-squelettique multi-corps (MCM). Due à l’insuffisance des données dans la cohorte pédiatrique, ce cadre a été mis en place pour l'articulation de l'épaule adulte. Pour cela, la précision de la MSF a été illustrée en prédisant 1) la forme de l'omoplate pré-morbide, et 2) les régions d'insertion musculaire sur l'omoplate et l'humérus. Cette méthode a ensuite été intégrée aux modèles MCM pour l'épaule adulte pour souligner l’importance des modèles spécifique-patient pour l’usage clinique. Pour le second objectif de cette thèse, j'ai développé un modèle MCM pédiatrique du complexe articulaire de l'épaule en utilisant le logiciel OpenSim. Grâce aux approches de cinématique et dynamique inverse, le modèle a permis de déterminer les différences de dynamique articulaires entre le côté sain et le côté pathologique. Les travaux futurs seront axés sur l’extension du travail réalisé pour la population pédiatrique afin de comprendre la pathomécanique de POPB
Obstetrician Brachial Plexus Palsy (OBPP) is a common birth injury in children leading to shoulder joint deformity and abnormal function. While the management of OBPP disorder focuses on restoring the shoulder joint function, the underlying pathomechanics is not clearly understood yet. Computational models are effective to provide such insights, however, there is no pediatric shoulder joint model to understand the OBPP disorder. Thus, the global aim of this research work was to build a computational framework combining the advances in statistical shape modeling (SSM) and multi-body musculoskeletal modeling (MSKM) domains. Due to a lack of sufficient data in the pediatric cohort, I first developed the framework for adult shoulder joint. For this, I illustrated the accuracy of SSM in predicting 1) missing part of the scapula, and 2) muscle insertion regions on scapula and humerus bones. This method was then integrated with adult shoulder MSKMs to show the differences between generic and subject specific constructs. For the second aim of this thesis, I developed a pediatric MSKM of the shoulder joint complex using OpenSim software. Pediatric MSKM represented scapulothoracic, sternoclavicular, acromioclavicular, and glenohumeral joints with 13 degrees of freedom, and actuated by 52 musculotendon actuators representing 14 shoulder muscles. Using inverse kinematics and inverse dynamics approaches, the model was used to determine the differences in joint kinematics, and joint dynamics between healthy and unhealthy side of a single OBPP subject. Future work is focused on completing the framework on pediatric population and understanding the pathomechanics of OBPP
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Patenaude, Brian Matthew. "Bayesian statistical models of shape and appearance for subcortical brain segmentation." Thesis, University of Oxford, 2007. http://ora.ox.ac.uk/objects/uuid:52f5fee0-60e8-4387-9560-728843e187b3.

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Our motivation is to develop an automated technique for the segmentation of sub-cortical human brain structures from MR images. To this purpose, models of shape-and-appearance are constructed and fit to new image data. The statistical models are trained from 317 manually labelled T1-weighted MR images. Shape is modelled using a surface-based point distribution model (PDM) such that the shape space is constrained to the linear combination of the mean shape and eigenvectors of the vertex coordinates. In addition, to model intensity at the structural boundary, intensities are sampled along the surface normal from the underlying image. We propose a novel Bayesian appearance model whereby the relationship between shape and intensity are modelled via the conditional distribution of intensity given shape. Our fully probabilistic approach eliminates the need for arbitrary weightings between shape and intensity as well as for tuning parameters that specify the relative contribution between the use of shape constraints and intensity information. Leave-one-out cross-validation is used to validate the model and fitting for 17 structures. The PDM for shape requires surface parameterizations of the volumetric, manual labels such that vertices retain a one-to-one correspondence across the training subjects. Surface parameterizations with correspondence are generated through the use of deformable models under constraints that embed the correspondence criterion within the deformation process. A novel force that favours equal-area triangles throughout the mesh is introduced. The force adds stability to the mesh such that minimal smoothing or within-surface motion is required. The use of the PDM for segmentation across a series of subjects results in a set surfaces that retain point correspondence. The correspondence facilitates landmark-based shape analysis. Amongst other metrics, vertex-wise multivariate statistics and discriminant analysis are used to investigate local and global size and shape differences between groups. The model is fit, and shape analysis is applied to two clinical datasets.
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López, Picazo Mirella. "3D subject-specific shape and density modeling of the lumbar spine from 2D DXA images for osteoporosis assessment." Doctoral thesis, Universitat Pompeu Fabra, 2019. http://hdl.handle.net/10803/666513.

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Osteoporosis is the most common bone disease, with a significant morbidity and mortality caused by the increase of bone fragility and susceptibility to fracture. Dual Energy X-ray Absorptiometry (DXA) is the gold standard technique for osteoporosis and fracture risk evaluation at the spine. However, the standard analysis of DXA images only provides 2D measurements and does not differentiate between bone compartments; neither specifically assess bone density in the vertebral body, which is where most of the osteoporotic fractures occur. Quantitative Computed Tomography (QCT) is an alternative technique that overcomes limitations of DXA-based diagnosis. However, due to the high cost and radiation dose, QCT is not used for osteoporosis management. In this thesis, a method providing a 3D subject-specific shape and density estimation of the lumbar spine from a single anteroposterior DXA image is proposed. The method is based on a 3D statistical shape and density model built from a training set of QCT scans. The 3D subject-specific shape and density estimation is obtained by registering and fitting the statistical model onto the DXA image. Cortical and trabecular bone compartments are segmented using a model-based algorithm. 3D measurements are performed at different vertebral regions and bone compartments. The accuracy of the proposed methods is evaluated by comparing DXA-derived to QCT-derived 3D measurements. Two case-control studies are also performed: a retrospective study evaluating the ability of DXA-derived 3D measurements at lumbar spine to discriminate between osteoporosis-related vertebral fractures and control groups; and a study evaluating the association between DXA-derived 3D measurements at lumbar spine and osteoporosis-related hip fractures. In both studies, stronger associations are found between osteoporosis-related fractures and DXA-derived 3D measurements compared to standard 2D measurements. The technology developed within this thesis offers an insightful 3D analysis of the lumbar spine, which could potentially improve osteoporosis and fracture risk assessment in patients who had a standard DXA scan of the lumbar spine without any additional examination.
La osteoporosis es la enfermedad ósea más común, con una morbilidad y mortalidad significativas causadas por el aumento de la fragilidad ósea y la susceptibilidad a las fracturas. La absorciometría de rayos X de energía dual (DXA, por sus siglas en inglés) es la técnica de referencia para la evaluación de la osteoporosis y del riesgo de fracturas en la columna vertebral. Sin embargo, el análisis estándar de las imágenes DXA solo proporciona mediciones 2D y no diferencia entre los compartimentos óseos; tampoco evalúa la densidad ósea en el cuerpo vertebral, que es donde se producen la mayoría de las fracturas osteoporóticas. La tomografía computarizada cuantitativa (QCT, por sus siglas en inglés) es una técnica alternativa que supera las limitaciones del diagnóstico basado en DXA. Sin embargo, debido al alto costo y la dosis de radiación, la QCT no se usa para el diagnóstico de la osteoporosis. En esta tesis, se propone un método que proporciona una estimación personalizada de la forma 3D y la densidad de la columna vertebral en la zona lumbar a partir de una única imagen DXA anteroposterior. El método se basa en un modelo estadístico 3D de forma y densidad creado a partir de un conjunto de entrenamiento de exploraciones QCT. La estimación 3D personalizada de forma y densidad se obtiene al registrar y ajustar el modelo estadístico con la imagen DXA. Se segmentan los compartimentos óseos corticales y trabeculares utilizando un algoritmo basado en modelos. Se realizan mediciones 3D en diferentes regiones vertebrales y compartimentos óseos. La precisión de los métodos propuestos se evalúa comparando las mediciones 3D derivadas de DXA con las derivadas de QCT. También se realizan dos estudios de casos y controles: un estudio retrospectivo que evalúa la capacidad de las mediciones 3D derivadas de DXA en la columna lumbar para discriminar entre sujetos con fracturas vertebrales relacionadas con la osteoporosis y sujetos control; y un estudio que evalúa la asociación entre las mediciones 3D derivadas de DXA en la columna lumbar y las fracturas de cadera relacionadas con la osteoporosis. En ambos estudios, se encuentran asociaciones más fuertes entre las fracturas relacionadas con la osteoporosis y las mediciones 3D derivadas de DXA en comparación con las mediciones estándar 2D. La tecnología desarrollada dentro de esta tesis ofrece un análisis en 3D de la columna lumbar, que podría mejorar la evaluación de la osteoporosis y el riesgo de fractura en pacientes que se sometieron a una exploración DXA estándar de la columna lumbar sin ningún examen adicional.
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Hoogendoorn, Corné. "A statistical dynamic cardiac atlas for the virtual physiological human: construction and application." Doctoral thesis, Universitat Pompeu Fabra, 2014. http://hdl.handle.net/10803/132632.

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This thesis is centered on the construction of a cardiac atlas to serve as a common reference frame in the Virtual Physiological Human (VPH). The construction covers the entire construction pipeline, starting from a set of 3D+t multislice computed tomography images, then performing a spatial normalization of these images, segmentation of the synthesized mean image, multi-structure meshing, and finally mapping of the mesh back to the population of images. In addition, two applications are presented in this thesis. First, the atlas is used to frame a spatio-temporal model of cardiac morphology which models the variability along both 'axes' simultaneously. Such a unified approach should be preferable over existing methods, which decouple the two sources of variation and then model them separately, in isolation. Second, the proposed atlas is applied to develop an acceleration technique for performing personalized simulation of cardiac electrophysiology (EP). The prior knowledge encapsulated in our atlas is used, in conjunction with a numerical solver of cardiac EP, to build a statistical model linking cardiac morphology with the steady states of myocardial cell models that pre condition detailed cardiac EP simulations. This application puts the proposed dynamic cardiac atlas in the context of VPH-related simulations, of which the computational costs are currently greatly in excess of what is acceptable for their adoption in current clinical practice.
Esta tesis está centrada en la construcción de un atlas cardiaco, para servir como marco común de referencia en el Virtual Physiological Human (VPH). La construcción consiste en la trayectoria completa, empezando con un conjunto de imágenes 3D+t de tomografía computacional multi-corte, y entonces hacer una normalización espacial de las imágenes, segmentación de la imagen promedio sintetizada, un mallado multi-estructura, y finalmente la transformación de la malla a la población de imágenes. Adicionalmente, la tesis presenta dos aplicaciones del atlas. Primero, el atlas se usa para enmarcar un modelo espacio-temporal de la morfología cardiaca que modela la variación a lo largo de ambos 'ejes' simultáneamente. Tal propuesta debe ser preferible sobre otros m\'etodos existentes, los cuales desacoplan las dos fuentes de variación para modelarlas separadamente, en isolación. Segundo, el atlas está aplicado al desarrollo de una técnica de aceleración para simulaciones personalizadas de electrofisiología (EF) cardiaca. El conocimiento previo encapsulado en nuestro atlas se usa, en conjunto con un solver de EF cardiaca, para construir un modelo estadístico conectando morfología cardiaca con los steady states de modelos celulares del miocardio que precondicionan a simulaciones detalladas de EF cardiaca. Esta aplicación posiciona el propuesto atlas dinámico cardiaco en el contexto de simulaciones relacionadas al VPH, cuyo costo computacional actual está en gran exceso de lo aceptable para su adopción en la práctica clínica de hoy en día.
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Su, Z. "Statistical shape modelling : automatic shape model building." Thesis, University College London (University of London), 2011. http://discovery.ucl.ac.uk/1213097/.

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Statistical Shape Models (SSM) have wide applications in image segmentation, surface registration and morphometry. This thesis deals with an important issue in SSM, which is establishing correspondence between a set of shape surfaces on either 2D or 3D. Current methods involve either manual annotation of the data (current ‘gold standard’); or establishing correspondences by using segmentation or registration algorithms; or using an information technique, Minimum Description Length (MDL), as an objective function that measures the utility of a model (the state-of-the-art). This thesis presents in principle another framework for establishing correspondences completely automatically by treating it as a learning process. Shannon theory is used extensively to develop an objective function, which measures the performance of a model along each eigenvector direction, and a proper weighting is automatically calculated for each energy component. Correspondence finding can then be treated as optimizing the objective function. An efficient optimization method is also incorporated by deriving the gradient of the cost function. Experimental results on various data are presented on both 2D and 3D. In the end, a quantitative evaluation between the proposed algorithm and MDL shows that the proposed model has better Generalization Ability, Specificity and similar Compactness. It also shows a good potential ability to solve the so-called “Pile Up” problem that exists in MDL. In terms of application, I used the proposed algorithm to help build a facial contour classifier. First, correspondence points across facial contours are found automatically and classifiers are trained by using the correspondence points found by the MDL, proposed method and direct human observer. These classification schemes are then used to perform gender prediction on facial contours. The final conclusion for the experiments is that MEM found correspondence points built classification scheme conveys a relatively more accurate gender prediction result. Although, we have explored the potential of our proposed method to some extent, this is not the end of the research for this topic. The future work is also clearly stated which includes more validations on various 3D datasets; discrimination analysis between normal and abnormal subjects could be the direct application for the proposed algorithm, extension to model-building using appearance information, etc.
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Zhu, Zuowei. "Modèles géométriques avec defauts pour la fabrication additive." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLN021/document.

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Les différentes étapes et processus de la fabrication additive (FA) induisent des erreurs de sources multiples et complexes qui soulèvent des problèmes majeurs au niveau de la qualité géométrique du produit fabriqué. Par conséquent, une modélisation effective des écarts géométriques est essentielle pour la FA. Le paradigme Skin Model Shapes (SMS) offre un cadre intégral pour la modélisation des écarts géométriques des produits manufacturés et constitue ainsi une solution efficace pour la modélisation des écarts géométriques en FA.Dans cette thèse, compte tenu de la spécificité de fabrication par couche en FA, un nouveau cadre de modélisation à base de SMS est proposé pour caractériser les écarts géométriques en FA en combinant une approche dans le plan et une approche hors plan. La modélisation des écarts dans le plan vise à capturer la variabilité de la forme 2D de chaque couche. Une méthode de transformation des formes est proposée et qui consiste à représenter les effets de variations sous la forme de transformations affines appliquées à la forme nominale. Un modèle paramétrique des écarts est alors établi dans un système de coordonnées polaires, quelle que soit la complexité de la forme. Ce modèle est par la suite enrichi par un apprentissage statistique permettant la collecte simultanée de données des écarts de formes multiples et l'amélioration des performances de la méthode.La modélisation des écarts hors plan est réalisée par la déformation de la couche dans la direction de fabrication. La modélisation des écarts hors plan est effectuée à l'aide d'une méthode orientée données. Sur la base des données des écarts obtenues à partir de simulations par éléments finis, deux méthodes d'analyse modale: la transformée en cosinus discrète (DCT) et l'analyse statistique des formes (SSA) sont exploitées. De plus, les effets des paramètres des pièces et des procédés sur les modes identifiés sont caractérisés par le biais d'un modèle à base de processus Gaussien.Les méthodes présentées sont finalement utilisées pour obtenir des SMSs haute-fidélité pour la fabrication additive en déformant les contours de la couche nominale avec les écarts prédits et en reconstruisant le modèle de surface non idéale complet à partir de ces contours déformés. Une toolbox est développée dans l'environnement MATLAB pour démontrer l'efficacité des méthodes proposées
The intricate error sources within different stages of the Additive Manufacturing (AM) process have brought about major issues regarding the dimensional and geometrical accuracy of the manufactured product. Therefore, effective modeling of the geometric deviations is critical for AM. The Skin Model Shapes (SMS) paradigm offers a comprehensive framework aiming at addressing the deviation modeling problem at different stages of product lifecycle, and is thus a promising solution for deviation modeling in AM. In this thesis, considering the layer-wise characteristic of AM, a new SMS framework is proposed which characterizes the deviations in AM with in-plane and out-of-plane perspectives. The modeling of in-plane deviation aims at capturing the variability of the 2D shape of each layer. A shape transformation perspective is proposed which maps the variational effects of deviation sources into affine transformations of the nominal shape. With this assumption, a parametric deviation model is established based on the Polar Coordinate System which manages to capture deviation patterns regardless of the shape complexity. This model is further enhanced with a statistical learning capability to simultaneously learn from deviation data of multiple shapes and improve the performance on all shapes.Out-of-plane deviation is defined as the deformation of layer in the build direction. A layer-level investigation of out-of-plane deviation is conducted with a data-driven method. Based on the deviation data collected from a number of Finite Element simulations, two modal analysis methods, Discrete Cosine Transform (DCT) and Statistical Shape Analysis (SSA), are adopted to identify the most significant deviation modes in the layer-wise data. The effect of part and process parameters on the identified modes is further characterized with a Gaussian Process (GP) model. The discussed methods are finally used to obtain high-fidelity SMSs of AM products by deforming the nominal layer contours with predicted deviations and rebuilding the complete non-ideal surface model from the deformed contours. A toolbox is developed in the MATLAB environment to demonstrate the effectiveness of the proposed methods
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Golalizadeh, Lehi Mousa. "Statistical modelling and inference for shape diffusions." Thesis, University of Nottingham, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.435446.

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Books on the topic "Statistical shape modeling"

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service), SpringerLink (Online, ed. First Principles Modelling of Shape Memory Alloys: Molecular Dynamics Simulations. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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(Editor), Hamid Krim, and Jr Anthony Yezzi (Editor), eds. Statistics and Analysis of Shapes (Modeling and Simulation in Science, Engineering and Technology). Birkhäuser Boston, 2006.

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Green, Peter, Kanti Mardia, Vysaul Nyirongo, and Yann Ruffieux. Bayesian modelling for matching and alignment of biomolecules. Edited by Anthony O'Hagan and Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.2.

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This article describes Bayesian modelling for matching and alignment of biomolecules. One particular task where statistical modelling and inference can be useful in scientific understanding of protein structure is that of matching and alignment of two or more proteins. In this regard, statistical shape analysis potentially has something to offer in solving biomolecule matching and alignment problems. The article discusses the use of Bayesian methods for shape analysis to assist with understanding the three-dimensional structure of protein molecules, with a focus on the problem of matching instances of the same structure in the CoMFA (Comparative Molecular Field Analysis) database of steroid molecules. It introduces a Bayesian hierarchical model for pairwise matching and for alignment of multiple configurations before concluding with an overview of some advantages of the Bayesian approach to problems in protein bioinformatics, along with modelling and computation issues, alternative approaches, and directions for future research.
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Kastner, Oliver. First Principles Modelling of Shape Memory Alloys: Molecular Dynamics Simulations. Springer, 2012.

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Kastner, Oliver. First Principles Modelling of Shape Memory Alloys: Molecular Dynamics Simulations. Springer Berlin / Heidelberg, 2014.

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Light, Ryan, and James Moody, eds. The Oxford Handbook of Social Networks. Oxford University Press, 2020. http://dx.doi.org/10.1093/oxfordhb/9780190251765.001.0001.

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Social networks fundamentally shape our lives. Networks channel the ways that information, emotions, and diseases flow through populations. Networks reflect differences in power and status in settings ranging from small peer groups to international relations across the globe. Network tools even provide insights into the ways that concepts, ideas and other socially generated contents shape culture and meaning. As such, the rich and diverse field of social network analysis has emerged as a central tool across the social sciences. This Handbook provides an overview of the theory, methods, and substantive contributions of this field. The thirty-three chapters move through the basics of social network analysis aimed at those seeking an introduction to advanced and novel approaches to modeling social networks statistically. The Handbook includes chapters on data collection and visualization, theoretical innovations, links between networks and computational social science, and how social network analysis has contributed substantively across numerous fields. As networks are everywhere in social life, the field is inherently interdisciplinary and this Handbook includes contributions from leading scholars in sociology, archaeology, economics, statistics, and information science among others.
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Aspden, Richard, and Jenny Gregory. Morphology. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199668847.003.0011.

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The study of joint morphology can help us to understand the risk factors for osteoarthritis (OA), how it progresses, and aids in developing imaging biomarkers for study of the disease. OA results in gross structural changes in affected joints. Growth of osteophytes, deformation of joint components, and loss of joint space where cartilage has broken down are all characteristics of the disorder. Certain bone shapes as well as malalignment predispose people to future OA, or may be a marker for early OA. Geometrical measures, such as the alpha angle or Wiberg’s CE angle, used to be the primary tool for investigating morphology. In recent years, however, statistical shape modelling (SSM) has become increasingly popular. SSM can be used with any imaging modality and has been successfully applied to a number of musculoskeletal conditions. It uses sets of landmark points denoting the anatomy of one or more bones to generate new variables (modes) that describe and quantify the shape variation in a set of images via principal components analysis. With the aid of automated search algorithms for point placement, the use of SSMs is expanding and provides a valuable and versatile tool for exploration of bone and joint morphometry. Whilst the majority of research has focused on hip and knee OA, this chapter provides an overview of joint morphology through the whole skeleton and how it has helped our ability to understand and quantify the risk and progression of osteoarthritis.
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Haig, Brian D. Exploratory Data Analysis. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190222055.003.0002.

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Chapter 2 is concerned with modern data analysis. It focuses primarily on the nature, role, and importance of exploratory data analysis, although it gives some attention to computer-intensive resampling methods. Exploratory data analysis is a process in which data are examined to reveal potential patterns of interest. However, the use of traditional confirmatory methods in data analysis remains the dominant practice. Different perspectives on data analysis, as they are shaped by four different accounts of scientific method, are provided. A brief discussion of John Tukey’s philosophy of teaching data analysis is presented. The chapter does not consider the more recent exploratory data analytic developments, such as the practice of statistical modeling, the employment of data-mining techniques, and more flexible resampling methods.
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Knepper, Paul, and Anja Johansen. Introduction. Edited by Paul Knepper and Anja Johansen. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780199352333.013.43.

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ThisHandbookoffers a systematic and comprehensive guide to the historical study of crime and criminal justice. It brings together essays written by researchers who work on crime and criminal justice in the past, with an emphasis on how the interaction between history and social sciences has shaped the field. It describes the methods of historical research, noting the potential, limitations, and pitfalls of these methods. Topics range from the modeling of crime trends to problems in interpretation of crime statistics, the geography of crime, organized crime and the cultural concept of the urban underworld, prostitution, retail theft, crime museums, and the role of women in Soviet criminology. There are also sections on police, courts, and prisons as major components of criminal justice. In addition, the volume explores how approaches to crime have been influenced by cultural assumptions about crime and violence in relation to gender. This introduction discusses the purpose, structure, and conceptual issues related to how theHandbookwas assembled.
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Book chapters on the topic "Statistical shape modeling"

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Srivastava, Anuj, and Eric P. Klassen. "Statistical Modeling on Nonlinear Manifolds." In Functional and Shape Data Analysis, 233–67. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-4020-2_7.

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Srivastava, Anuj, and Eric P. Klassen. "Statistical Modeling of Functional Data." In Functional and Shape Data Analysis, 269–303. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-4020-2_8.

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Srivastava, Anuj, and Eric P. Klassen. "Statistical Modeling of Planar Shapes." In Functional and Shape Data Analysis, 305–47. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-4020-2_9.

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Pohl, Kilian M., Simon K. Warfield, Ron Kikinis, W. Eric L. Grimson, and William M. Wells. "Coupling Statistical Segmentation and PCA Shape Modeling." In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004, 151–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30135-6_19.

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Yang, Yuhui, Anthony Bull, Daniel Rueckert, and Adam Hill. "3D Statistical Shape Modeling of Long Bones." In Biomedical Image Registration, 306–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11784012_37.

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Ma, Jingting, Feng Lin, Jonas Honsdorf, Katharina Lentzen, Stefan Wesarg, and Marius Erdt. "Weighted Robust PCA for Statistical Shape Modeling." In Lecture Notes in Computer Science, 343–53. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-43775-0_31.

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Taghizadeh, Elham, Alexandre Terrier, Fabio Becce, Alain Farron, and Philippe Büchler. "Segmenting Bones Using Statistical Shape Modeling and Local Template Matching." In Shape in Medical Imaging, 189–94. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04747-4_18.

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Frangi, A. F., D. Rueckert, J. A. Schnabel, and W. J. Niessen. "Automatic Construction of Biventricular Statistical Shape Models." In Functional Imaging and Modeling of the Heart, 18–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-44883-7_3.

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Hufnagel, Heike. "Current Methods in Statistical Shape Analysis." In A Probabilistic Framework for Point-Based Shape Modeling in Medical Image Analysis, 7–25. Wiesbaden: Vieweg+Teubner Verlag, 2011. http://dx.doi.org/10.1007/978-3-8348-8600-2_2.

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Bhalodia, Riddhish, Shireen Y. Elhabian, Ladislav Kavan, and Ross T. Whitaker. "DeepSSM: A Deep Learning Framework for Statistical Shape Modeling from Raw Images." In Shape in Medical Imaging, 244–57. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04747-4_23.

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Conference papers on the topic "Statistical shape modeling"

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Velasco-Forero, Santiago, and Jesus Angulo. "Statistical Shape Modeling Using Morphological Representations." In 2010 20th International Conference on Pattern Recognition (ICPR). IEEE, 2010. http://dx.doi.org/10.1109/icpr.2010.863.

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Vaswani, N., A. R. Chowdhury, and R. Chellappa. "Statistical shape theory for activity modeling." In 2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698). IEEE, 2003. http://dx.doi.org/10.1109/icme.2003.1221278.

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"FACIAL EXPRESSION RECOGNITION USING LOG-EUCLIDEAN STATISTICAL SHAPE MODELS." In Special Session on Shape Analysis and Deformable Modeling. SciTePress - Science and and Technology Publications, 2012. http://dx.doi.org/10.5220/0003867503510359.

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"A STATISTICAL APPROACH TO BUILD 3D PROTOTYPES FROM A 3D ANTHROPOMETRIC SURVEY OF THE SPANISH FEMALE POPULATION." In Special Session on Shape Analysis and Deformable Modeling. SciTePress - Science and and Technology Publications, 2012. http://dx.doi.org/10.5220/0003876803700374.

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Li, Kang, Xiaoping Qian, and Alejandro A. Espinoza Orías. "Efficient Construction of Statistical Shape Models for Patient-Specific Modeling." In ASME 2013 Conference on Frontiers in Medical Devices: Applications of Computer Modeling and Simulation. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/fmd2013-16113.

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Statistical Shape Modeling (SSM) is a powerful tool to capture the shape variation pattern across a group of shapes belonging to a certain shape class. SSM has seen many promising applications for the purpose of building Patient-Specific Model (PSM) because it avoids unwanted exposure to ionizing radiation from imaging modalities such as CT scanning and has potential as a cost-saving and time-efficient research and clinical tool. All that is needed to reconstruct the patient — specific data is to instantiate the statistical model already generated. The utility of the statistical model relies on a sufficiently large training set data pool from as many patients as possible; and more importantly, a reasonably good correspondence across the entire training set. As such, the description length has been used as a standard to measure the quality of correspondence and the statistical model, and the desired correspondence found by optimization. However, the previously proposed optimization schemes are too inefficient to be used for large data sets. We present a new optimization scheme based on B-spline freeform deformation and analytical adjoint sensitivity. This scheme is significantly more efficient in that it makes use of: 1) extraordinary efficiency of direct correspondence manipulation; 2) availability of analytical gradient due to the differentiable shapes and correspondence manipulation; 3) superiority of adjoint method when a large number of design variables are used in optimization. In the experimental part, we compare the efficiency of our method and current method for some benchmark examples where solutions are known. Additionally, we show the statistical models for a 3D distal femur bone training set. Such models have been previously used in osteosarcoma cases as a bone bank for bone allografts, where shape-matching is very important [1]. The graphical illustration of the training set and preliminary results of the obtained statistical modes are displayed in Figure 1, 2, 3, 4 and 5.
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Hollenbeck, Justin F. M., Paul J. Rullkoetter, Christopher Cain, Clare K. Fitzpatrick, and Peter J. Laz. "Statistical Shape and Alignment Modeling of the Lumbar Spine." In ASME 2013 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/sbc2013-14337.

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The mechanics of the lumbar spine are dependent on the morphology of the vertebral bodies and their alignment. As intersubject anatomic variability is significant, this paper developed a method to characterize shape and alignment variability in the lumbar spine using statistical shape modeling techniques. The primary modes of variation between subjects were sagittal plane curvature of the spine and height of the discs. Quantifying the biomechanical variation of the lumbar spine across the population facilitates designers and clinicians in making informed decisions regarding implant sizing and component placement.
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Zewail, Rami, Ahmed Elsafi, and Nelson Durdle. "Wavelet-Based Independent Component Analysis For Statistical Shape Modeling." In 2007 Canadian Conference on Electrical and Computer Engineering. IEEE, 2007. http://dx.doi.org/10.1109/ccece.2007.299.

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Palmer, Robert Ieuan, Xianghua Xie, and Gary Tam. "Finding complete 3D vertex correspondence for statistical shape modeling." In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2015. http://dx.doi.org/10.1109/embc.2015.7319001.

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Dalal, Pahal, Brent C. Munsell, Song Wang, Jijun Tang, Kenton Oliver, Hiroaki Ninomiya, Xiangrong Zhou, and Hiroshi Fujita. "A Fast 3D Correspondence Method for Statistical Shape Modeling." In CVPR '07. IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 2007. http://dx.doi.org/10.1109/cvpr.2007.383143.

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Dalal, Pahal, Lili Ju, Michael McLaughlin, Xiangrong Zhou, Hiroshi Fujita, and Song Wang. "3D open-surface shape correspondence for statistical shape modeling: Identifying topologically consistent landmarks." In 2009 IEEE 12th International Conference on Computer Vision (ICCV). IEEE, 2009. http://dx.doi.org/10.1109/iccv.2009.5459412.

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