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Statistical Shape and Deformation Analysis

Statistical Shape and Deformation Analysis
Methods, Implementation and Applications

by Guoyan Zheng,Shuo Li,Gabor Szekely

  • Publisher : Academic Press
  • Release : 2017-03-23
  • Pages : 508
  • ISBN : 0128104945
  • Language : En, Es, Fr & De
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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

Exam Prep for: Statistical Shape and Deformation Analysis

Exam Prep for: Statistical Shape and Deformation Analysis
A Book

by Anonim

  • Publisher : Unknown Publisher
  • Release : 2021
  • Pages : 329
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Statistical Shape Analysis

Statistical Shape Analysis
A Book

by Ian L.. Dryden,Ian L. Dryden,Kanti V. Mardia

  • Publisher : Wiley-Blackwell
  • Release : 1998-09-16
  • Pages : 347
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Thos book involves methods for the geometrical study of random objects where location, rotation and scale information.

Statistical Shape Analysis

Statistical Shape Analysis
With Applications in R

by Ian L. Dryden,Kanti V. Mardia

  • Publisher : John Wiley & Sons
  • Release : 2016-06-28
  • Pages : 496
  • ISBN : 1119072506
  • Language : En, Es, Fr & De
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A thoroughly revised and updated edition of this introduction to modern statistical methods for shape analysis Shape analysis is an important tool in the many disciplines where objects are compared using geometrical features. Examples include comparing brain shape in schizophrenia; investigating protein molecules in bioinformatics; and describing growth of organisms in biology. This book is a significant update of the highly-regarded `Statistical Shape Analysis’ by the same authors. The new edition lays the foundations of landmark shape analysis, including geometrical concepts and statistical techniques, and extends to include analysis of curves, surfaces, images and other types of object data. Key definitions and concepts are discussed throughout, and the relative merits of different approaches are presented. The authors have included substantial new material on recent statistical developments and offer numerous examples throughout the text. Concepts are introduced in an accessible manner, while retaining sufficient detail for more specialist statisticians to appreciate the challenges and opportunities of this new field. Computer code has been included for instructional use, along with exercises to enable readers to implement the applications themselves in R and to follow the key ideas by hands-on analysis. Statistical Shape Analysis: with Applications in R will offer a valuable introduction to this fast-moving research area for statisticians and other applied scientists working in diverse areas, including archaeology, bioinformatics, biology, chemistry, computer science, medicine, morphometics and image analysis .

Riemannian Geometric Statistics in Medical Image Analysis

Riemannian Geometric Statistics in Medical Image Analysis
A Book

by Xavier Pennec,Stefan Sommer,Tom Fletcher

  • Publisher : Academic Press
  • Release : 2019-09
  • Pages : 636
  • ISBN : 0128147253
  • Language : En, Es, Fr & De
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Over the past 15 years, there has been a growing need in the medical image computing community for principled methods to process nonlinear geometric data. Riemannian geometry has emerged as one of the most powerful mathematical and computational frameworks for analyzing such data. Riemannian Geometric Statistics in Medical Image Analysis is a complete reference on statistics on Riemannian manifolds and more general nonlinear spaces with applications in medical image analysis. It provides an introduction to the core methodology followed by a presentation of state-of-the-art methods. Content includes: - The foundations of Riemannian geometric methods for statistics on manifolds with emphasis on concepts rather than on proofs - Applications of statistics on manifolds and shape spaces in medical image computing - Diffeomorphic deformations and their applications As the methods described apply to domains such as signal processing (radar signal processing and brain computer interaction), computer vision (object and face recognition), and other domains where statistics of geometric features appear, this book is suitable for researchers and graduate students in medical imaging, engineering and computer science. - A complete reference covering both the foundations and state-of-the-art methods - Edited and authored by leading researchers in the field - Contains theory, examples, applications, and algorithms - Gives an overview of current research challenges and future applications

Shape Analysis in Medical Image Analysis

Shape Analysis in Medical Image Analysis
A Book

by Shuo Li,João Manuel R. S. Tavares

  • Publisher : Springer Science & Business Media
  • Release : 2014-01-28
  • Pages : 442
  • ISBN : 3319038133
  • Language : En, Es, Fr & De
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This book contains thirteen contributions from invited experts of international recognition addressing important issues in shape analysis in medical image analysis, including techniques for image segmentation, registration, modelling and classification and applications in biology, as well as in cardiac, brain, spine, chest, lung and clinical practice. This volume treats topics such as for example, anatomic and functional shape representation and matching; shape-based medical image segmentation; shape registration; statistical shape analysis; shape deformation; shape-based abnormity detection; shape tracking and longitudinal shape analysis; machine learning for shape modeling and analysis; shape-based computer-aided-diagnosis; shape-based medical navigation; benchmark and validation of shape representation, analysis and modeling algorithms. This work will be of interest to researchers, students and manufacturers in the fields of artificial intelligence, bioengineering, biomechanics, computational mechanics, computational vision, computer sciences, human motion, mathematics, medical imaging, medicine, pattern recognition and physics.

Intelligent Orthopaedics

Intelligent Orthopaedics
Artificial Intelligence and Smart Image-guided Technology for Orthopaedics

by Guoyan Zheng,Wei Tian,Xiahai Zhuang

  • Publisher : Springer
  • Release : 2018-10-10
  • Pages : 359
  • ISBN : 9811313962
  • Language : En, Es, Fr & De
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This book introduces readers to the latest technological advances in the emerging field of intelligent orthopaedics. Artificial intelligence and smart instrumentation techniques are now revolutionizing every area of our lives, including medicine. The applications of these techniques in orthopaedic interventions offer a number of potential benefits, e.g. reduced incision size and scarring, minimized soft tissue damage, and decreased risk of misalignment. Consequently, these techniques have become indispensable for various orthopaedic interventions, which has led to the emerging field of intelligent orthopaedics. Addressing key technologies and applications, this book offers a valuable guide for all researchers and clinicians who need an update on both the principles and practice of intelligent orthopaedics, and for graduate students embarking on a career in this field.​

Shape in Medical Imaging

Shape in Medical Imaging
International Workshop, ShapeMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings

by Martin Reuter,Christian Wachinger,Hervé Lombaert,Beatriz Paniagua,Marcel Lüthi,Bernhard Egger

  • Publisher : Springer
  • Release : 2018-11-22
  • Pages : 312
  • ISBN : 3030047474
  • Language : En, Es, Fr & De
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This book constitutes the proceedings of the Workshop on Shape in Medical Imaging, ShapeMI 2018, held in conjunction with the 21st International Conference on Medical Image Computing, MICCAI 2018, in Granada, Spain, in September 2018. The 26 full papers and 2 short papers presented were carefully reviewed and selected for inclusion in this volume. The papers discuss novel approaches and applications in shape and geometry processing and their use in research and clinical studies and explore novel, cutting-edge theoretical methods and their usefulness for medical applications, e.g., from the fields of geometric learning or spectral shape analysis.

Image Correlation for Shape, Motion and Deformation Measurements

Image Correlation for Shape, Motion and Deformation Measurements
Basic Concepts,Theory and Applications

by Michael A. Sutton,Jean Jose Orteu,Hubert Schreier

  • Publisher : Springer Science & Business Media
  • Release : 2009-04-21
  • Pages : 322
  • ISBN : 038778747X
  • Language : En, Es, Fr & De
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Image Correlation for Shape, Motion and Deformation Measurements provides a comprehensive overview of data extraction through image analysis. Readers will find and in-depth look into various single- and multi-camera models (2D-DIC and 3D-DIC), two- and three-dimensional computer vision, and volumetric digital image correlation (VDIC). Fundamentals of accurate image matching are described, along with presentations of both new methods for quantitative error estimates in correlation-based motion measurements, and the effect of out-of-plane motion on 2D measurements. Thorough appendices offer descriptions of continuum mechanics formulations, methods for local surface strain estimation and non-linear optimization, as well as terminology in statistics and probability. With equal treatment of computer vision fundamentals and techniques for practical applications, this volume is both a reference for academic and industry-based researchers and engineers, as well as a valuable companion text for appropriate vision-based educational offerings.

Elastic Shape Analysis of Three-Dimensional Objects

Elastic Shape Analysis of Three-Dimensional Objects
A Book

by Ian H. Jermyn,Sebastian Kurtek,Hamid Laga,Anuj Srivastava

  • Publisher : Morgan & Claypool Publishers
  • Release : 2017-09-15
  • Pages : 185
  • ISBN : 1681730286
  • Language : En, Es, Fr & De
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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.

Functional and Shape Data Analysis

Functional and Shape Data Analysis
A Book

by Anuj Srivastava,Eric P. Klassen

  • Publisher : Springer
  • Release : 2016-10-03
  • Pages : 447
  • ISBN : 1493940201
  • Language : En, Es, Fr & De
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This textbook for courses on function data analysis and shape data analysis describes how to define, compare, and mathematically represent shapes, with a focus on statistical modeling and inference. It is aimed at graduate students in analysis in statistics, engineering, applied mathematics, neuroscience, biology, bioinformatics, and other related areas. The interdisciplinary nature of the broad range of ideas covered—from introductory theory to algorithmic implementations and some statistical case studies—is meant to familiarize graduate students with an array of tools that are relevant in developing computational solutions for shape and related analyses. These tools, gleaned from geometry, algebra, statistics, and computational science, are traditionally scattered across different courses, departments, and disciplines; Functional and Shape Data Analysis offers a unified, comprehensive solution by integrating the registration problem into shape analysis, better preparing graduate students for handling future scientific challenges. Recently, a data-driven and application-oriented focus on shape analysis has been trending. This text offers a self-contained treatment of this new generation of methods in shape analysis of curves. Its main focus is shape analysis of functions and curves—in one, two, and higher dimensions—both closed and open. It develops elegant Riemannian frameworks that provide both quantification of shape differences and registration of curves at the same time. Additionally, these methods are used for statistically summarizing given curve data, performing dimension reduction, and modeling observed variability. It is recommended that the reader have a background in calculus, linear algebra, numerical analysis, and computation.

Information Processing in Medical Imaging

Information Processing in Medical Imaging
17th International Conference, IPMI 2001, Davis, CA, USA, June 18-22, 2001. Proceedings

by Michael F. Insana,Richard M. Leahy

  • Publisher : Springer
  • Release : 2003-06-29
  • Pages : 544
  • ISBN : 3540457291
  • Language : En, Es, Fr & De
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This book constitutes the refereed proceedings of the 17th International Conference on Information Processing in Medical Imaging, IPMI 2001, held in Davis, CA, USA, in June 2001. The 54 revised papers presented were carefully reviewed and selected from 78 submissions. The papers are organized in topical sections on objective assessment of image quality, shape modeling, molecular and diffusion tensor imaging, registration and structural analysis, functional image analysis, fMRI/EEG/MEG, deformable registration, shape analysis, and analysis of brain structure.

3D Shape Analysis

3D Shape Analysis
Fundamentals, Theory, and Applications

by Hamid Laga,Yulan Guo,Hedi Tabia,Robert B. Fisher,Mohammed Bennamoun

  • Publisher : Wiley
  • Release : 2019-01-07
  • Pages : 352
  • ISBN : 1119405106
  • Language : En, Es, Fr & De
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An in-depth description of the state-of-the-art of 3D shape analysis techniques and their applications This book discusses the different topics that come under the title of "3D shape analysis". It covers the theoretical foundations and the major solutions that have been presented in the literature. It also establishes links between solutions proposed by different communities that studied 3D shape, such as mathematics and statistics, medical imaging, computer vision, and computer graphics. The first part of 3D Shape Analysis: Fundamentals, Theory, and Applications provides a review of the background concepts such as methods for the acquisition and representation of 3D geometries, and the fundamentals of geometry and topology. It specifically covers stereo matching, structured light, and intrinsic vs. extrinsic properties of shape. Parts 2 and 3 present a range of mathematical and algorithmic tools (which are used for e.g., global descriptors, keypoint detectors, local feature descriptors, and algorithms) that are commonly used for the detection, registration, recognition, classification, and retrieval of 3D objects. Both also place strong emphasis on recent techniques motivated by the spread of commodity devices for 3D acquisition. Part 4 demonstrates the use of these techniques in a selection of 3D shape analysis applications. It covers 3D face recognition, object recognition in 3D scenes, and 3D shape retrieval. It also discusses examples of semantic applications and cross domain 3D retrieval, i.e. how to retrieve 3D models using various types of modalities, e.g. sketches and/or images. The book concludes with a summary of the main ideas and discussions of the future trends. 3D Shape Analysis: Fundamentals, Theory, and Applications is an excellent reference for graduate students, researchers, and professionals in different fields of mathematics, computer science, and engineering. It is also ideal for courses in computer vision and computer graphics, as well as for those seeking 3D industrial/commercial solutions.

Deformation Analysis in Soft Ground Improvement

Deformation Analysis in Soft Ground Improvement
A Book

by Jinchun Chai,John P. Carter

  • Publisher : Springer Science & Business Media
  • Release : 2011-07-14
  • Pages : 250
  • ISBN : 9789400717213
  • Language : En, Es, Fr & De
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This book deals with the behaviour of soft ground improved by some of the more common methods, including the installation of prefabricated vertical drains (PVDs), or the installation of soil-cement columns formed by deep mixing, or the preloading of soft ground by application of a vacuum pressure in addition to, or instead of, a surcharge loading. In particular, it describes the theories and the numerical modelling techniques that may be applied to these soft ground improvement schemes to estimate the immediate and time-dependent mechanical response of the in situ soil. Particular emphasis has been placed on methods that reliably predict ground deformations associated with ground improvement techniques. The book commences with a brief description of the various ground improvement methods and then describes general techniques for modelling the behaviour of soft clay subsoils by the finite element method, as well as details of the methods for modelling soft soils improved by the installation of PVDs. It also includes chapters describing the theory of vacuum consolidation and methods for calculating vacuum pressure-induced ground deformation, as well as a theory which can be used to predict the response of soft ground improved by the installation of soil-cement columns. An important distinguishing feature of this book is the routine use of comparisons of predictions of the proposed models with the results of laboratory studies, and particularly field case studies, in order to validate the proposed methods of analysis. The field case histories are from soft soil sites at various locations around the world. The book is directed towards students of geotechnical engineering as well as geotechnical practitioners. In the main it provides complete derivations of most of the important theoretical results, as the intention was to write a book that could be used as both a teaching text and a reference work for students and practitioners. Audience: The book is intended for geotechnical practitioners as well as for students.

Medical Imaging

Medical Imaging
Image processing

by Anonim

  • Publisher : Unknown Publisher
  • Release : 1999
  • Pages : 329
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Computer Analysis of Images and Patterns

Computer Analysis of Images and Patterns
13th International Conference, CAIP 2009, Münster, Germany, September 2-4, 2009, Proceedings

by Xiaoyi Jiang,Nicolai Petkov

  • Publisher : Springer Science & Business Media
  • Release : 2009-08-28
  • Pages : 1249
  • ISBN : 3642037666
  • Language : En, Es, Fr & De
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This book constitutes the refereed proceedings of the bienially held International Conference on Computer Analysis of Images and Patterns, CAIP 2009, which took place in Münster, Germany, September 2-4, 2009. The 148 papers presented together with 2 invited talks were carefully reviewed and selected from 405 submissions. The papers are organized in topical section on: biometrics, calibration, document analysis, features, graph representations, image processing, image registration, image and video retrieval, medical imaging, object and scene recognition, pattern recognition, shape recovery, segmentation, stereo and video analysis, texture analysis, and applications.

Information Processing in Medical Imaging

Information Processing in Medical Imaging
Proceedings of the ... Conference

by Anonim

  • Publisher : Unknown Publisher
  • Release : 2001
  • Pages : 329
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Spectral and Shape Analysis in Medical Imaging

Spectral and Shape Analysis in Medical Imaging
First International Workshop, SeSAMI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Revised Selected Papers

by Martin Reuter,Christian Wachinger,Hervé Lombaert

  • Publisher : Springer
  • Release : 2016-12-10
  • Pages : 133
  • ISBN : 3319512374
  • Language : En, Es, Fr & De
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This book constitutes the refereed post-conference proceedings of the First International Workshop on Spectral and Shape Analysis in Medical Imaging, SeSAMI 2016, held in conjunction with MICCAI 2016, in Athens, Greece, in October 2016. The 10 submitted full papers presented in this volume were carefully reviewed. The papers reflect the following topics: spectral methods; longitudinal methods; and shape methods.

A Probabilistic Framework for Point-Based Shape Modeling in Medical Image Analysis

A Probabilistic Framework for Point-Based Shape Modeling in Medical Image Analysis
A Book

by Heike Hufnagel

  • Publisher : Springer Science & Business Media
  • Release : 2011-11-23
  • Pages : 147
  • ISBN : 3834886009
  • Language : En, Es, Fr & De
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Heike Hufnagel develops a mathematically sound statistical shape model. Due to the particular attributes of the model, the challenging integration of explicit and implicit representations can be performed in an elegant mathematical formulation, thus combining the advantages of both explicit model and implicit segmentation method.

Proceedings, 12th International Conference on Image Analysis and Processing

Proceedings, 12th International Conference on Image Analysis and Processing
Mantova, Italy, September 17 to 19, 2003

by Anonim

  • Publisher : Institute of Electrical & Electronics Engineers(IEEE)
  • Release : 2003
  • Pages : 691
  • ISBN : 9780769519487
  • Language : En, Es, Fr & De
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The organization of the ICIAP 2003 proceedings reflects the main topics of the Conference: shape analysis and reconstruction, 3D models, early vision and image analysis, pattern recognition and image inference, visual processing for communication and various application domains. The major topics discussed in the text are on use of image analysis and processing techniques and tools both in standard application environments and in the new scenario of internet based delivery of information.