Differential Geometry Methods for Biomedical Image Processing PDF Download

Author: David Rivest-Hénault
Publisher:
ISBN: 9780494788844
Category :
Languages : en
Pages :

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Author: Ravikanth Malladi
Publisher: Springer Science & Business Media
ISBN: 3642559875
Category : Mathematics
Languages : en
Pages : 151

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Book Description
The genesis of this book goes back to the conference held at the University of Bologna, June 1999, on collaborative work between the University of California at Berkeley and the University of Bologna. The book, in its present form, is a compilation of some of the recent work using geometric partial differential equations and the level set methodology in medical and biomedical image analysis. The book not only gives a good overview on some of the traditional applications in medical imagery such as, CT, MR, Ultrasound, but also shows some new and exciting applications in the area of Life Sciences, such as confocal microscope image understanding.

Author: Xavier Pennec
Publisher: Academic Press
ISBN: 0128147261
Category : Computers
Languages : en
Pages : 636

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Book Description
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. Beyond medical image computing, the methods described in this book may also apply to other domains such as signal processing, computer vision, geometric deep learning, and other domains where statistics on geometric features appear. As such, the presented core methodology takes its place in the field of geometric statistics, the statistical analysis of data being elements of nonlinear geometric spaces. The foundational material and the advanced techniques presented in the later parts of the book can be useful in domains outside medical imaging and present important applications of geometric statistics methodology 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

Author: Li M. Chen
Publisher: Springer
ISBN: 3319120999
Category : Computers
Languages : en
Pages : 325

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Book Description
This book provides comprehensive coverage of the modern methods for geometric problems in the computing sciences. It also covers concurrent topics in data sciences including geometric processing, manifold learning, Google search, cloud data, and R-tree for wireless networks and BigData. The author investigates digital geometry and its related constructive methods in discrete geometry, offering detailed methods and algorithms. The book is divided into five sections: basic geometry; digital curves, surfaces and manifolds; discretely represented objects; geometric computation and processing; and advanced topics. Chapters especially focus on the applications of these methods to other types of geometry, algebraic topology, image processing, computer vision and computer graphics. Digital and Discrete Geometry: Theory and Algorithms targets researchers and professionals working in digital image processing analysis, medical imaging (such as CT and MRI) and informatics, computer graphics, computer vision, biometrics, and information theory. Advanced-level students in electrical engineering, mathematics, and computer science will also find this book useful as a secondary text book or reference. Praise for this book: This book does present a large collection of important concepts, of mathematical, geometrical, or algorithmical nature, that are frequently used in computer graphics and image processing. These concepts range from graphs through manifolds to homology. Of particular value are the sections dealing with discrete versions of classic continuous notions. The reader finds compact definitions and concise explanations that often appeal to intuition, avoiding finer, but then necessarily more complicated, arguments... As a first introduction, or as a reference for professionals working in computer graphics or image processing, this book should be of considerable value." - Prof. Dr. Rolf Klein, University of Bonn.

Author: J. Andreas Bærentzen
Publisher: Springer Science & Business Media
ISBN: 1447140753
Category : Computers
Languages : en
Pages : 330

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Book Description
This book reviews the algorithms for processing geometric data, with a practical focus on important techniques not covered by traditional courses on computer vision and computer graphics. Features: presents an overview of the underlying mathematical theory, covering vector spaces, metric space, affine spaces, differential geometry, and finite difference methods for derivatives and differential equations; reviews geometry representations, including polygonal meshes, splines, and subdivision surfaces; examines techniques for computing curvature from polygonal meshes; describes algorithms for mesh smoothing, mesh parametrization, and mesh optimization and simplification; discusses point location databases and convex hulls of point sets; investigates the reconstruction of triangle meshes from point clouds, including methods for registration of point clouds and surface reconstruction; provides additional material at a supplementary website; includes self-study exercises throughout the text.

Author: David Wilson
Publisher: Springer Science & Business Media
ISBN: 0306485516
Category : Medical
Languages : en
Pages : 661

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Book Description
Handbook of Biomedical Image Analysis: Segmentation Models (Volume I) is dedicated to the segmentation of complex shapes from the field of imaging sciences using different mathematical techniques. This volume is aimed at researchers and educators in imaging sciences, radiological imaging, clinical and diagnostic imaging, physicists covering different medical imaging modalities, as well as researchers in biomedical engineering, applied mathematics, algorithmic development, computer vision, signal processing, computer graphics and multimedia in general, both in academia and industry . Key Features: - Principles of intra-vascular ultrasound (IVUS) - Principles of positron emission tomography (PET) - Physical principles of magnetic resonance angiography (MRA). - Basic and advanced level set methods - Shape for shading method for medical image analysis - Wavelet transforms and other multi-scale analysis functions - Three dimensional deformable surfaces - Level Set application for CT lungs, brain MRI and MRA volume segmentation - Segmentation of incomplete tomographic medical data sets - Subjective level sets for missing boundaries for segmentation

Author: Jasjit S. Suri
Publisher: Springer Science & Business Media
ISBN: 9780306486074
Category : Computers
Languages : en
Pages : 978

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Book Description
With rapid advancements in technology, body imaging or components thereof, have become ubiquitous in medicine. While the biomedical devices such as the MRI, CT, X-rays, Ultrasound, PET/SPECT and Microscopy etc, provide us with high resolution images, the challenges that have continued to confront us with, lie in the interpretation of the vast amounts of data generated by these devices. Biomedical applications are the 'bottom-line' essentials in the diagnostic world. It is this diagnostic interpretation feature that forms the core niche for these books and will serve the needs of a broad spectrum of audience including researchers, research clinicians, and students.Together the three volumesnbsp;will illustrate the role of the fusion of registration and segmentation systems for complete biomedical applications therapy delivery benefiting the biomedical doctors, clinical researchers, radiologists and others.

Author:
Publisher: Elsevier
ISBN: 0444642064
Category : Mathematics
Languages : en
Pages : 157

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Book Description
Processing, Analyzing and Learning of Images, Shapes, and Forms: Volume 19, Part One provides a comprehensive survey of the contemporary developments related to the analysis and learning of images, shapes and forms. It covers mathematical models as well as fast computational techniques, and includes new chapters on Alternating diffusion: a geometric approach for sensor fusion, Shape Correspondence and Functional Maps, Geometric models for perception-based image processing, Decomposition schemes for nonconvex composite minimization: theory and applications, Low rank matrix recovery: algorithms and theory, Geometry and learning for deformation shape correspondence, and Factoring scene layout from monocular images in presence of occlusion. Presents a contemporary view on the topic, comprehensively covering the newest developments and content Provides a comprehensive survey of the contemporary developments related to the analysis and learning of images, shapes and forms

Author: J. Andreas Bærentzen
Publisher: Springer
ISBN: 9781447160311
Category : Computers
Languages : en
Pages : 326

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Book Description
This book reviews the algorithms for processing geometric data, with a practical focus on important techniques not covered by traditional courses on computer vision and computer graphics. Features: presents an overview of the underlying mathematical theory, covering vector spaces, metric space, affine spaces, differential geometry, and finite difference methods for derivatives and differential equations; reviews geometry representations, including polygonal meshes, splines, and subdivision surfaces; examines techniques for computing curvature from polygonal meshes; describes algorithms for mesh smoothing, mesh parametrization, and mesh optimization and simplification; discusses point location databases and convex hulls of point sets; investigates the reconstruction of triangle meshes from point clouds, including methods for registration of point clouds and surface reconstruction; provides additional material at a supplementary website; includes self-study exercises throughout the text.

Author: Stanley Osher
Publisher: Springer Science & Business Media
ISBN: 0387218106
Category : Computers
Languages : en
Pages : 523

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Book Description
Here is, for the first time, a book that clearly explains and applies new level set methods to problems and applications in computer vision, graphics, and imaging. It is an essential compilation of survey chapters from the leading researchers in the field. The applications of the methods are emphasized.