Download or read book Statistical Shape Modeling for Custom Design and Analysis written by Xilu Wang and published by . This book was released on 2017 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of this dissertation research is to use pre-existing shape data to improve efficiency and quality of custom design and analysis. The rapid advancement of sensor miniaturization and growing sensor networks and computer power has lead to wide availability of massive shape data from populations of objects. Such massive shape data range from human body shapes to longitudinal knee observations of osteoarthritis patients. Populations of shape data also include shapes of man-made objects, such as part shapes of the same model due to manufacturing process variation as well as part shapes due to shape degradation after deployment. Mining and analysis of such massive population-based shape data can result in knowledge of shape variability of the population and lead to the construction of faithful subject-specific 3D shape models from sparse measurements. It is then possible to predict shape-specific functional performance and population-wide structural performance variation. Such an ability brings about unprecedented capabilities and tantalizing opportunities for mass customization, part-specific failure prediction and just-in-time part maintenance, and patient-specific biomedical intervention and treatment. This work aims at developing efficient approaches that can: 1) construct faithful subject-specific shape models from sparse measurements; 2) predict shape-specific structural performance from a given subject-specific shape model; and 3) predict structural performance variation over a shape population. Toward this end, we present a statistical atlas based approach that incorporates statistical shape modeling in subject-specific shape reconstruction, finite element (FE) modeling and analysis. The statistical atlas contains three parts: the mean shape and the variation modes of the shape population which span a linear shape space, the FE mesh of the mean shape, and the selected feature points and sizing dimensions. The feature points and sizing dimensions are selected by maximizing the total variance they capture of the shape population. Given a subject (e.g. a person), the corresponding dimensions are measured and the subject specific shape model is synthesized. The FE mesh of the mean shape serves as the template mesh which can be morphed to the subject shape to conduct subject-specific FE analysis. The FE solution on the template mesh can also be extrapolated to the subject shape through Taylor expansion. The shape variances along the variation modes are obtained by the principal component analysis. These variances tell the amount of shape variabilities in the population and are combined with the Taylor expansion of the FE solution to obtain the structural performance variation across the population. The numerical testings with various 2D and 3D shape databases demonstrate the efficiency and effectiveness of the proposed approach for custom design and analysis. In this dissertation a statistical atlas based framework is developed for custom design and analysis. The main contributions of this work are: 1) An approach that selects feature points and sizing dimensions based on the total variance captured of the shape population. 2) Automated subject-specific FE modeling through mesh morphing based on the shape correspondence obtained by searching in the shape space. A multi-correlation based metric is developed to evaluate the quality of the obtained shape correspondences. 3) A Taylor expansion approach for predicting subject-specific structural performance and computing structural performance variation over a shape population. Multi-point Taylor expansion approach is developed for the cases that the structural performance is highly nonlinear with respect to the shape parameters.

Download or read book Innovations for Shape Analysis written by Michael Breuß and published by Springer Science & Business Media. This book was released on 2013-04-04 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: The concept of 'shape' is at the heart of image processing and computer vision, yet researchers still have some way to go to replicate the human brain's ability to extrapolate meaning from the most basic of outlines. This volume reflects the advances of the last decade, which have also opened up tough new challenges in image processing. Today's applications require flexible models as well as efficient, mathematically justified algorithms that allow data processing within an acceptable timeframe. Examining important topics in continuous-scale and discrete modeling, as well as in modern algorithms, the book is the product of a key seminar focused on innovations in the field. It is a thorough introduction to the latest technology, especially given the tutorial style of a number of chapters. It also succeeds in identifying promising avenues for future research. The topics covered include mathematical morphology, skeletonization, statistical shape modeling, continuous-scale shape models such as partial differential equations and the theory of discrete shape descriptors. Some authors highlight new areas of enquiry such as partite skeletons, multi-component shapes, deformable shape models, and the use of distance fields. Combining the latest theoretical analysis with cutting-edge applications, this book will attract both academics and engineers.

Download or read book Medical Image Computing and Computer Assisted Intervention MICCAI 2008 written by Dimitris Metaxas and published by Springer. This book was released on 2008-09-10 with total page 1136 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 11th International Conference on Medical Imaging and Computer Assisted Intervention, MICCAI 2008, was held at the Helen and Martin Kimmel Center of New York University, New York City, USA on September 6–10, 2008. MICCAI is the premier international conference in this domain, with - depth papers on the multidisciplinary ?elds of biomedical image computing and analysis, computer assisted intervention and medical robotics. The conference brings together biological scientists, clinicians, computer scientists, engineers, mathematicians, physicists and other interested researchers and o?ers them a forum to exchange ideas in these exciting and rapidly growing ?elds. The conference is both very selective and very attractive: this year we - ceived a record number of 700 submissions from 34 countries and 6 continents, fromwhich258papers were selectedfor publication,whichcorrespondsto a s- cess rate of approximately 36%. Some interesting facts about the distribution of submitted and accepted papers are shown graphically at the end of this preface. The paper selection process this year was based on the following procedure, which included the introduction of several novelties over previous years. 1. A ProgramCommittee (PC) of 49 members was recruited by the Program Chairs,to getthenecessarybody ofexpertiseandgeographicalcoverage.All PC members agreed in advance to participate in the ?nal paper selection process. 2. Key words grouped in 7 categories were used to describe the content of the submissions and the expertise of the reviewers.

Download or read book Design Tools and Methods in Industrial Engineering II written by Caterina Rizzi and published by Springer Nature. This book was released on 2021-12-01 with total page 968 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers original papers reporting on innovative methods and tools in design, modelling, simulation and optimization, and their applications in engineering design, manufacturing and other relevant industrial sectors. Topics span from advances in geometric modelling, applications of virtual reality, innovative strategies for product development and additive manufacturing, human factors and user-centered design, engineering design education and applications of engineering design methods in medical rehabilitation and cultural heritage. Chapters are based on contributions to the Second International Conference on Design Tools and Methods in Industrial Engineering, ADM 2021, held on September 9–10, 2021, in Rome, Italy, and organized by the Italian Association of Design Methods and Tools for Industrial Engineering, and Dipartimento di Ingegneria Meccanica e Aerospaziale of Sapienza Università di Roma, Italy. All in all, this book provides academics and professionals with a timely overview and extensive information on trends and technologies in industrial design and manufacturing.

Download or read book Statistical Models of Shape written by Rhodri Davies and published by Springer Science & Business Media. This book was released on 2008-12-15 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of image interpretation is to convert raw image data into me- ingful information. Images are often interpreted manually. In medicine, for example, a radiologist looks at a medical image, interprets it, and tra- lates the data into a clinically useful form. Manual image interpretation is, however, a time-consuming, error-prone, and subjective process that often requires specialist knowledge. Automated methods that promise fast and - jective image interpretation have therefore stirred up much interest and have become a signi?cant area of research activity. Early work on automated interpretation used low-level operations such as edge detection and region growing to label objects in images. These can p- ducereasonableresultsonsimpleimages,butthepresenceofnoise,occlusion, andstructuralcomplexity oftenleadstoerroneouslabelling. Furthermore,- belling an object is often only the ?rst step of the interpretation process. In order to perform higher-level analysis, a priori information must be incor- rated into the interpretation process. A convenient way of achieving this is to use a ?exible model to encode information such as the expected size, shape, appearance, and position of objects in an image. The use of ?exible models was popularized by the active contour model, or ‘snake’ [98]. A snake deforms so as to match image evidence (e.g., edges) whilst ensuring that it satis?es structural constraints. However, a snake lacks speci?city as it has little knowledge of the domain, limiting its value in image interpretation.

Download or read book Statistical Shape and Deformation Analysis written by Guoyan Zheng and published by Academic Press. This book was released on 2017-03-23 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Shape and Deformation Analysis: Methods, Implementation and Applications contributes enormously to solving different problems in patient care and physical anthropology, ranging from improved automatic registration and segmentation in medical image computing to the study of genetics, evolution and comparative form in physical anthropology and biology. This book gives a clear description of the concepts, methods, algorithms and techniques developed over the last three decades that is followed by examples of their implementation using open source software. Applications of statistical shape and deformation analysis are given for a wide variety of fields, including biometry, anthropology, medical image analysis and clinical practice. - Presents an accessible introduction to the basic concepts, methods, algorithms and techniques in statistical shape and deformation analysis - Includes implementation examples using open source software - Covers real-life applications of statistical shape and deformation analysis methods

Download or read book Statistical Shape Models in Image Analysis written by K. V. Mardia and published by . This book was released on 1992 with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt: We discuss several models for shapes in the plane based on the distributions of landmarks about an underlying template. The motivation for these models includes Markov random fields and thin plate splines. These models are used as priors in a Bayesian framework to reconstruct a shape from a digital image. An example is given based on the human hand.

Download or read book Geometric Morphometrics for Biologists written by Miriam Zelditch and published by Academic Press. This book was released on 2012-08-02 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first edition of Geometric Morphometrics for Biologists has been the primary resource for teaching modern geometric methods of shape analysis to biologists who have a stronger background in biology than in multivariate statistics and matrix algebra. These geometric methods are appealing to biologists who approach the study of shape from a variety of perspectives, from clinical to evolutionary, because they incorporate the geometry of organisms throughout the data analysis. The second edition of this book retains the emphasis on accessible explanations, and the copious illustrations and examples of the first, updating the treatment of both theory and practice. The second edition represents the current state-of-the-art and adds new examples and summarizes recent literature, as well as provides an overview of new software and step-by-step guidance through details of carrying out the analyses. Contains updated coverage of methods, especially for sampling complex curves and 3D forms and a new chapter on applications of geometric morphometrics to forensics Offers a reorganization of chapters to streamline learning basic concepts Presents detailed instructions for conducting analyses with freely available, easy to use software Provides numerous illustrations, including graphical presentations of important theoretical concepts and demonstrations of alternative approaches to presenting results

Download or read book Elastic Shape Analysis of Three Dimensional Objects written by Ian H. Jermyn and published by Morgan & Claypool Publishers. This book was released on 2017-09-15 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical analysis of shapes of 3D objects is an important problem with a wide range of applications. This analysis is difficult for many reasons, including the fact that objects differ in both geometry and topology. In this manuscript, we narrow the problem by focusing on objects with fixed topology, say objects that are diffeomorphic to unit spheres, and develop tools for analyzing their geometries. The main challenges in this problem are to register points across objects and to perform analysis while being invariant to certain shape-preserving transformations. We develop a comprehensive framework for analyzing shapes of spherical objects, i.e., objects that are embeddings of a unit sphere in R, including tools for: quantifying shape differences, optimally deforming shapes into each other, summarizing shape samples, extracting principal modes of shape variability, and modeling shape variability associated with populations. An important strength of this framework is that it is elastic: it performs alignment, registration, and comparison in a single unified framework, while being invariant to shape-preserving transformations. The approach is essentially Riemannian in the following sense. We specify natural mathematical representations of surfaces of interest, and impose Riemannian metrics that are invariant to the actions of the shape-preserving transformations. In particular, they are invariant to reparameterizations of surfaces. While these metrics are too complicated to allow broad usage in practical applications, we introduce a novel representation, termed square-root normal fields (SRNFs), that transform a particular invariant elastic metric into the standard L2 metric. As a result, one can use standard techniques from functional data analysis for registering, comparing, and summarizing shapes. Specifically, this results in: pairwise registration of surfaces; computation of geodesic paths encoding optimal deformations; computation of Karcher means and covariances under the shape metric; tangent Principal Component Analysis (PCA) and extraction of dominant modes of variability; and finally, modeling of shape variability using wrapped normal densities. These ideas are demonstrated using two case studies: the analysis of surfaces denoting human bodies in terms of shape and pose variability; and the clustering and classification of the shapes of subcortical brain structures for use in medical diagnosis. This book develops these ideas without assuming advanced knowledge in differential geometry and statistics. We summarize some basic tools from differential geometry in the appendices, and introduce additional concepts and terminology as needed in the individual chapters.

Download or read book Perspectives in Shape Analysis written by Michael Breuß and published by Springer. This book was released on 2016-09-30 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advances in the field of shape analysis. Written by experts in the fields of continuous-scale shape analysis, discrete shape analysis and sparsity, and numerical computing who hail from different communities, it provides a unique view of the topic from a broad range of perspectives. Over the last decade, it has become increasingly affordable to digitize shape information at high resolution. Yet analyzing and processing this data remains challenging because of the large amount of data involved, and because modern applications such as human-computer interaction require real-time processing. Meeting these challenges requires interdisciplinary approaches that combine concepts from a variety of research areas, including numerical computing, differential geometry, deformable shape modeling, sparse data representation, and machine learning. On the algorithmic side, many shape analysis tasks are modeled using partial differential equations, which can be solved using tools from the field of numerical computing. The fields of differential geometry and deformable shape modeling have recently begun to influence shape analysis methods. Furthermore, tools from the field of sparse representations, which aim to describe input data using a compressible representation with respect to a set of carefully selected basic elements, have the potential to significantly reduce the amount of data that needs to be processed in shape analysis tasks. The related field of machine learning offers similar potential. The goal of the Dagstuhl Seminar on New Perspectives in Shape Analysis held in February 2014 was to address these challenges with the help of the latest tools related to geometric, algorithmic and numerical concepts and to bring together researchers at the forefront of shape analysis who can work together to identify open problems and novel solutions. The book resulting from this seminar will appeal to researchers in the field of shape analysis, image and vision, from those who want to become more familiar with the field, to experts interested in learning about the latest advances.​

Download or read book Statistical Shape Analysis for Bio structures written by Daniel Alejandro Valdés Amaro and published by . This book was released on 2009 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Statistical Atlases and Computational Models of the Heart Imaging and Modelling Challenges written by Oscar Camara and published by Springer. This book was released on 2016-01-08 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-workshop proceedings of the 6th International Workshop on Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges, STACOM 2015, held in conjunction with MICCAI 2015, in Munich, Germany, in October 2015. The 23 revised full workshop papers were carefully reviewed and selected from 34 submissions. The papers cover a wide range of topics such cardiac image processing, atlas construction, statistical modeling of cardiac function across different patient populations, cardiac mapping, cardiac computational physiology, model customization, image-based modelling and image-guided interventional procedures, atlas based functional analysis, ontological schemata for data and results, integrated functional and structural analysis.

Download or read book Design for Manufacturability and Statistical Design written by Michael Orshansky and published by Springer Science & Business Media. This book was released on 2007-10-28 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design for Manufacturability and Statistical Design: A Comprehensive Approach presents a comprehensive overview of methods that need to be mastered in understanding state-of-the-art design for manufacturability and statistical design methodologies. Broadly, design for manufacturability is a set of techniques that attempt to fix the systematic sources of variability, such as those due to photolithography and CMP. Statistical design, on the other hand, deals with the random sources of variability. Both paradigms operate within a common framework, and their joint comprehensive treatment is one of the objectives of this book and an important differentation.

Download or read book Handbook of Pattern Recognition and Computer Vision 5th Edition written by Chi-hau Chen and published by World Scientific. This book was released on 2015-12-15 with total page 582 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides an up-to-date and authoritative treatment of pattern recognition and computer vision, with chapters written by leaders in the field. On the basic methods in pattern recognition and computer vision, topics range from statistical pattern recognition to array grammars to projective geometry to skeletonization, and shape and texture measures. Recognition applications include character recognition and document analysis, detection of digital mammograms, remote sensing image fusion, and analysis of functional magnetic resonance imaging data, etc.

Download or read book Statistical Design written by George Casella and published by Springer Science & Business Media. This book was released on 2008-04-03 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical design is one of the fundamentals of our subject, being at the core of the growth of statistics during the previous century. In this book the basic theoretical underpinnings are covered. It describes the principles that drive good designs and good statistics. Design played a key role in agricultural statistics and set down principles of good practice, principles that still apply today. Statistical design is all about understanding where the variance comes from, and making sure that is where the replication is. Indeed, it is probably correct to say that these principles are even more important today.

Download or read book Proceedings of the 11th International Conference on Soft Computing and Pattern Recognition SoCPaR 2019 written by Ajith Abraham and published by Springer Nature. This book was released on 2020-07-31 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights recent research on soft computing, pattern recognition and biologically inspired computing. It presents 24 selected papers from the 11th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2019) and 5 papers from the 11th World Congress on Nature and Biologically Inspired Computing (NaBIC 2019), held at Vardhaman College of Engineering, Hyderabad, India, on December 13–15, 2019. SoCPaR–NaBIC is a premier conference and brings together researchers, engineers and practitioners whose work involves soft computing and bio-inspired computing, as well as their industrial and real-world applications. Including contributions by authors from 15 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.

Download or read book Statistical Shape Analysis Using Deformetrica written by Mithun Acharjee and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical shape analysis is an emerging field of research that analyzes the geometrical properties of a given set of shapes or objects using different statistical methods. Two important aspects of the shape analysis are to estimate the mean shape from a given set of shapes and to estimate a shape trajectory as close as to the observed shapes in order to determine the continuous evaluation of shapes over time. A deterministic Atlas model is used to compute the mean shape (also referred to as atlas construction) from a set of shapes which builds a generalization of a typical representation by preserving the characteristics of the original shapes. Thus mean shape is useful in forecasting trends in form or pulling out stereotypes from a set of homologous shapes. The Geodesic regression is used to estimate the continuous shape evaluation at a certain time within its intervals where the mean face obtained from the deterministic atlas model can be used as baseline shape or initial template face to initiate the program. In this thesis, we are showing the application of the deterministic atlas model and geodesic regression model using a shape analysis software called Deformetrica. We collected data from the three Dimensional Facial Norm (3DFN) database which provides craniofacial anthropometric normative data deposited in the FaceBase consortium. Our data are 3D facial mesh where each facial mesh contains a high number of landmark points. We applied the deterministic atlas model using Deformetrica accessing the GPU allocation, which helps to estimate the mean facial object. We used this mean facial object as an initial template shape on geodesic regression which provides an estimated shape trajectory of the facial objects. This geodesic shape trajectory is a geodesic flow of diffeomorphisms acting on the above baseline template shape to estimate the continuous 3D facial evaluation with age varying continuously within its range. This thesis also describes the technical details of using Deformetrica in a high-performance computing environment while dealing a 3D geometric objects with a high number of landmark points.