Magnetic Resonance Image Reconstruction PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Magnetic Resonance Image Reconstruction PDF full book. Access full book title Magnetic Resonance Image Reconstruction by Mehmet Akcakaya. Download full books in PDF and EPUB format.
Author: Mehmet Akcakaya
Publisher: Academic Press
ISBN: 012822746X
Category : Science
Languages : en
Pages : 518
Get Book Here
Book Description
Magnetic Resonance Image Reconstruction: Theory, Methods and Applications presents the fundamental concepts of MR image reconstruction, including its formulation as an inverse problem, as well as the most common models and optimization methods for reconstructing MR images. The book discusses approaches for specific applications such as non-Cartesian imaging, under sampled reconstruction, motion correction, dynamic imaging and quantitative MRI. This unique resource is suitable for physicists, engineers, technologists and clinicians with an interest in medical image reconstruction and MRI. - Explains the underlying principles of MRI reconstruction, along with the latest research - Gives example codes for some of the methods presented - Includes updates on the latest developments, including compressed sensing, tensor-based reconstruction and machine learning based reconstruction
Author: Mehmet Akcakaya
Publisher: Academic Press
ISBN: 012822746X
Category : Science
Languages : en
Pages : 518
Get Book Here
Book Description
Magnetic Resonance Image Reconstruction: Theory, Methods and Applications presents the fundamental concepts of MR image reconstruction, including its formulation as an inverse problem, as well as the most common models and optimization methods for reconstructing MR images. The book discusses approaches for specific applications such as non-Cartesian imaging, under sampled reconstruction, motion correction, dynamic imaging and quantitative MRI. This unique resource is suitable for physicists, engineers, technologists and clinicians with an interest in medical image reconstruction and MRI. - Explains the underlying principles of MRI reconstruction, along with the latest research - Gives example codes for some of the methods presented - Includes updates on the latest developments, including compressed sensing, tensor-based reconstruction and machine learning based reconstruction
Author: A.P. Korostelev
Publisher: Springer Science & Business Media
ISBN: 1461227127
Category : Mathematics
Languages : en
Pages : 272
Get Book Here
Book Description
There exists a large variety of image reconstruction methods proposed by different authors (see e. g. Pratt (1978), Rosenfeld and Kak (1982), Marr (1982)). Selection of an appropriate method for a specific problem in image analysis has been always considered as an art. How to find the image reconstruction method which is optimal in some sense? In this book we give an answer to this question using the asymptotic minimax approach in the spirit of Ibragimov and Khasminskii (1980a,b, 1981, 1982), Bretagnolle and Huber (1979), Stone (1980, 1982). We assume that the image belongs to a certain functional class and we find the image estimators that achieve the best order of accuracy for the worst images in the class. This concept of optimality is rather rough since only the order of accuracy is optimized. However, it is useful for comparing various image reconstruction methods. For example, we show that some popular methods such as simple linewise processing and linear estimation are not optimal for images with sharp edges. Note that discontinuity of images is an important specific feature appearing in most practical situations where one has to distinguish between the "image domain" and the "background" . The approach of this book is based on generalization of nonparametric regression and nonparametric change-point techniques. We discuss these two basic problems in Chapter 1. Chapter 2 is devoted to minimax lower bounds for arbitrary estimators in general statistical models.
Author: Barry S. Cooper
Publisher: Springer
ISBN: 3642308708
Category : Computers
Languages : en
Pages : 773
Get Book Here
Book Description
This book constitutes the refereed proceedings of the Turing Centenary Conference and the 8th Conference on Computability in Europe, CiE 2012, held in Cambridge, UK, in June 2012. The 53 revised papers presented together with 6 invited lectures were carefully reviewed and selected with an acceptance rate of under 29,8%. The CiE 2012 Turing Centenary Conference will be remembered as a historic event in the continuing development of the powerful explanatory role of computability across a wide spectrum of research areas. The papers presented at CiE 2012 represent the best of current research in the area, and forms a fitting tribute to the short but brilliant trajectory of Alan Mathison Turing. Both the conference series and the association promote the development of computability-related science, ranging over mathematics, computer science and applications in various natural and engineering sciences such as physics and biology, and also including the promotion of related non-scientific fields such as philosophy and history of computing.
Author: Gustavo Deco
Publisher: Springer Science & Business Media
ISBN: 9780387946665
Category : Computers
Languages : en
Pages : 288
Get Book Here
Book Description
Neural networks provide a powerful new technology to model and control nonlinear and complex systems. In this book, the authors present a detailed formulation of neural networks from the information-theoretic viewpoint. They show how this perspective provides new insights into the design theory of neural networks. In particular they show how these methods may be applied to the topics of supervised and unsupervised learning including feature extraction, linear and non-linear independent component analysis, and Boltzmann machines. Readers are assumed to have a basic understanding of neural networks, but all the relevant concepts from information theory are carefully introduced and explained. Consequently, readers from several different scientific disciplines, notably cognitive scientists, engineers, physicists, statisticians, and computer scientists, will find this to be a very valuable introduction to this topic.
Author: Kevin H. Knuth
Publisher: American Institute of Physics
ISBN:
Category : Computers
Languages : en
Pages : 586
Get Book Here
Book Description
All papers were peer-reviewed. For over 25 years the MaxEnt workshops have explored Bayesian and Maximum Entropy methods in scientific, engineering, and signal processing applications. This proceedings volume covers all aspects of probabilistic inference such as techniques, applications, and foundations. Applications include physics, space science, earth science, biology, imaging, graphical models and source separation.
Author: Leondes
Publisher: CRC Press
ISBN: 9789056996109
Category : Technology & Engineering
Languages : en
Pages : 360
Get Book Here
Book Description
The field of modalities has been revolutionized by powerful new computational techniques in image processing, with applications such as Computer-Aided Tomography (CAT) and Magnetic Resonance Imaging (MRI), among others. It is, therefore, an appropriate topic to be included in this series that studies the marriage of computer capabilities and medical imaging, exemplifying a significant illustration of relatively recent, valuable technologies known as the second industrial revolution. Examines the issues, challenges, technology, and progress of 3-D imaging, SPECT reconstruction, gastrointestinal endoscopy, and EIT. Also explores the techniques, methods and issues involving accurate quantification of neuroreceptor-binding radioglands, and reconstructing images from the four types of incompleteness that arise in computed tomography: truncated projections, hollow projections, limited angle coverage, and arbitrarily missing values in a projection. This book clearly reveals the effectiveness and gre
Author:
Publisher: Mercury Learning and Information
ISBN: 1683920767
Category : Science
Languages : en
Pages : 5057
Get Book Here
Book Description
This digital collection of twelve book length titles encompasses all of the major subject areas of physics. All twelve titles are combined into one easily downloadable file and are fully-searchable in a Web.pdf, bookmarked, file format. Titles include electromagnetism, particle physics, quantum mechanics, theory of relativity, mathematical methods for physics, computational physics, electrical engineering experiments, multiphysics modeling, solid state physics, radio astronomy, Newtonian mechanics, and physics lab experiments. FEATURES: • Includes 12 full length book titles in one, fully searchable, Web.pdf file • Each book title is preceded by a descriptive page with overview and features • All titles include the complete front matter, text, and end matter from the original printed version • Over 5000 pages of physics information in one file • Complete file downloads in less than two minutes LIST OF TITLES Particle Physics. Robert Purdy, PhD Mathematical Methods for Physics Using MATLAB and Maple. J. Claycomb, PhD The Special Theory of Relativity. Dennis Morris, PhD Computational Physics. Darren Walker, PhD Quantum Mechanics. Dennis Morris, PhD Basic Electromagnetic Theory. James Babington, PhD Physics Lab Experiments. Matthew M. J. French, PhD Newtonian Mechanics. Derek Raine, PhD Solid State Physics. David Schmool, PhD Multiphysics Modeling Using COMSOL5 and MATLAB. R. Pryor, PhD Radio Astronomy. S. Joardar, PhD Electrical Engineering Experiments. G.P. Chhalotra, PhD
Author: S. Böhme
Publisher: Springer Science & Business Media
ISBN: 3662123401
Category : Science
Languages : en
Pages : 930
Get Book Here
Book Description
Astronomy and Astrophysics Abstracts aims to present a comprehensive documen tation of the literature concerning all aspects of astronomy, astrophysics, and their border fields. It is devoted to the recording, summarizing, and indexing of the relevant publications throughout the world. Astronomy and Astrophysics Abstracts is prepared by a special department of the Astronomisches Rechen-Institut under the auspices of the International Astronomical Union. Volume 34 records literature published in 1983 and received before February 17, 1984. Some older documents which we received late and which are not surveyed in earlier volumes are included too. We acknowledge with thanks contributions of our colleagues all over the world. We also express our gratitude to all organiza tions, observatories, and publishers which provide us with complimentary copies of their publications. Starting with Volume 33, all the recording, correction, and data processing work was done by means of computers. The recording was done by our technical staff members Ms. Helga Ballmann, Ms. Mona El-Choura and Ms. Monika Kohl. Mr. Martin Schlotelburg and Mr. Ulrich Oberall supported our task by careful proofreading. It is a pleasure to thank them all for their encouragement. Heidelberg, March 1984 The Editors Contents Introduction . . . . . . . . . . . . Concordance Relation: ICSU-AB-AAA 3 Abbreviations 10 Periodicals, Proceedings, Books, Activities 001 Periodicals . . . . . . . . . . . 15 002 Bibliographical Publications, Documentation, Catalogues, Atlases 50 003 Books ...... . 58 004 History of Astronomy 67 005 Biography . . 71 006 Personal Notes 73 007 Obituaries . . .
Author: STEPHEN LUTTRELL
Publisher: Stephen Luttrell
ISBN:
Category : Science
Languages : en
Pages : 508
Get Book Here
Book Description
The motivation for the research that is described in these volumes is the wish to explain things in terms of their underlying causes, rather than merely being satisfied with phenomenological descriptions. When this reductionist approach is applied to information processing it allows the internal structure of information to be analysed, so information processing algorithms can then be derived from first principles. One of the simplest examples of this approach is the diagonalisation of a data covariance matrix – there are many variants of this basic approach, such as singular value decomposition – in which the assumed independent components of high-dimensional data are identified and extracted. The main limitation of this type of information analysis approach is that it is based on linear algebra applied globally to the data space, so it is unable to preserve information about any local data structure in the data space. For instance, if the data lives on a low-dimensional curved manifold embedded in the data space, then only the global properties of this manifold would be preserved by global linear algebra methods. In practice, data whose high-dimensional structure is non-trivial typically lives on a noisy version of a curved manifold, so techniques for analysing such data must automatically handle this type of structure. For instance, a blurred image of a point source is described by its underlying degrees of freedom – i.e. the position of the source – and as the source moves about it generates a curved manifold that lives in the high-dimensional space of pixel values of the sampled image. The basic problem is then to deduce the internal properties of this manifold by analysing examples of such images. A more challenging problem would be to extend this analysis to images that contain several overlapping blurred images of point sources, and so on. There is no limit to the complexity of the types of high-dimensional data that one might want to analyse. These methods then need to be automated so that they do not rely on human intervention, which would then allow them to be inserted as “components” into information processing networks. The purpose of the research that is described in these volumes is to develop principled information processing methods that can be used for such analysis. Self-organising information processing networks arise naturally in this context, in which ways of cutting up the original manifold into simpler pieces emerge automatically.
Author: G. Erickson
Publisher: Springer Science & Business Media
ISBN: 9401090548
Category : Mathematics
Languages : en
Pages : 432
Get Book Here
Book Description
This volume has its origin in the Fifth, Sixth and Seventh Workshops on "Maximum-Entropy and Bayesian Methods in Applied Statistics", held at the University of Wyoming, August 5-8, 1985, and at Seattle University, August 5-8, 1986, and August 4-7, 1987. It was anticipated that the proceedings of these workshops would be combined, so most of the papers were not collected until after the seventh workshop. Because most of the papers in this volume are in the nature of advancing theory or solving specific problems, as opposed to status reports, it is believed that the contents of this volume will be of lasting interest to the Bayesian community. The workshop was organized to bring together researchers from different fields to critically examine maximum-entropy and Bayesian methods in science and engineering as well as other disciplines. Some of the papers were chosen specifically to kindle interest in new areas that may offer new tools or insight to the reader or to stimulate work on pressing problems that appear to be ideally suited to the maximum-entropy or Bayesian method. These workshops and their proceedings could not have been brought to their final form without the support or help of a number of people.
