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.
Download or read book Shape in Medical Imaging written by Martin Reuter and published by Springer. This book was released on 2018-11-22 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
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 Statistical Shape Analysis of Anatomical Structures written by Poilna Golland and published by . This book was released on 2001 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: (Cont.) For morphological studies, the discriminative direction can be conveniently represented by a deformation of the original shape, yielding an intuitive description of shape differences for visualization and further analysis. Based on this approach, we present a system for statistical shape analysis using distance transforms for shape representation and the Support Vector Machines learning algorithm for the optimal classifier estimation. We demonstrate it on artificially generated data sets, as well as real medical studies.
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 of Featureless Objects written by Asger Hobolth and published by . This book was released on 2002 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 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 model based computational biomechanics Applications in joints and internal organs written by Emmanuel A. Audenaert and published by Frontiers Media SA. This book was released on 2023-07-05 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Shape in Medical Imaging written by Christian Wachinger and published by Springer Nature. This book was released on 2023-10-30 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume comprises the proceedings of the International Workshop, ShapeMI 2023, which took place alongside MICCAI 2023 on October 8, 2023, in Vancouver, British Columbia, Canada. The 23 selected full papers deal with all aspects of leading methods and applications for advanced shape analysis and geometric learning in medical imaging.
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 Elastic Statistical Shape Analysis with Landmark Constraints written by Justin Strait and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to mathematical and computational advances, the study of shape data is of great interest in numerous fields, including biology, medicine, computer vision, and biometrics. Shape can be de fined as a property of an object which remains after removing variability associated with shape-preserving transformations, including translation, scale, rotation, and, in some cases, re-parameterization. This type of data presents mathematical challenges, as objects may have identical shape despite appearing differently in Euclidean space. The complex structure of shape data requires tools from fields such as differential geometry, algebra, and functional analysis.
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 0 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.
Download or read book Nonrigid Shape Correspondence for Statistical Shape Analysis written by Theodor Dan Richardson and published by . This book was released on 2006 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 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 Statistical Shape Analysis for Bilateral Symmetry written by Kolamunnage Dona Rasanga Ruwanthi and published by . This book was released on 2005 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt:
