Mathematical Modeling, Estimation, and Imaging 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 Mathematical Modeling, Estimation, and Imaging PDF full book. Access full book title Mathematical Modeling, Estimation, and Imaging by David C. Wilson. Download full books in PDF and EPUB format.
Author: David C. Wilson
Publisher: SPIE-International Society for Optical Engineering
ISBN:
Category : Computers
Languages : en
Pages : 262
Get Book Here
Book Description
Author: David C. Wilson
Publisher: SPIE-International Society for Optical Engineering
ISBN:
Category : Computers
Languages : en
Pages : 262
Get Book Here
Book Description
Author: Habib Ammari
Publisher: Springer Science & Business Media
ISBN: 3642034438
Category : Mathematics
Languages : en
Pages : 244
Get Book Here
Book Description
This volume gives an introduction to a fascinating research area to applied mathematicians. It is devoted to providing the exposition of promising analytical and numerical techniques for solving challenging biomedical imaging problems, which trigger the investigation of interesting issues in various branches of mathematics.
Author: Habib Ammari
Publisher: Springer Science & Business Media
ISBN: 3642229891
Category : Mathematics
Languages : en
Pages : 170
Get Book Here
Book Description
This volume reports on recent mathematical and computational advances in optical, ultrasound, and opto-acoustic tomographies. It outlines the state-of-the-art and future directions in these fields and provides readers with the most recently developed mathematical and computational tools. It is particularly suitable for researchers and graduate students in applied mathematics and biomedical engineering.
Author: Bernard Chalmond
Publisher: Springer Science & Business Media
ISBN: 0387216626
Category : Mathematics
Languages : en
Pages : 322
Get Book Here
Book Description
More mathematicians have been taking part in the development of digital image processing as a science and the contributions are reflected in the increasingly important role modeling has played solving complex problems. This book is mostly concerned with energy-based models. Most of these models come from industrial projects in which the author was involved in robot vision and radiography: tracking 3D lines, radiographic image processing, 3D reconstruction and tomography, matching, deformation learning. Numerous graphical illustrations accompany the text.
Author: Charles L. Epstein
Publisher: SIAM
ISBN: 9780898717792
Category : Mathematics
Languages : en
Pages : 794
Get Book Here
Book Description
At the heart of every medical imaging technology is a sophisticated mathematical model of the measurement process and an algorithm to reconstruct an image from the measured data. This book provides a firm foundation in the mathematical tools used to model the measurements and derive the reconstruction algorithms used in most of these modalities. The text uses X-ray computed tomography (X-ray CT) as a 'pedagogical machine' to illustrate important ideas and its extensive discussion of background material makes the more advanced mathematical topics accessible to people with a less formal mathematical education. This new edition contains a chapter on magnetic resonance imaging (MRI), a revised section on the relationship between the continuum and discrete Fourier transforms, an improved description of the gridding method, and new sections on both Grangreat's formula and noise analysis in MR-imaging. Mathematical concepts are illuminated with over 200 illustrations and numerous exercises.
Author: Zhengming Wang
Publisher: CRC Press
ISBN: 1439853797
Category : Computers
Languages : en
Pages : 540
Get Book Here
Book Description
This book discusses the theories, methods, and application techniques of the measurement data mathematical modeling and parameter estimation. It seeks to build a bridge between mathematical theory and engineering practice in the measurement data processing field so theoretical researchers and technical engineers can communicate. It is organized with abundant materials, such as illustrations, tables, examples, and exercises. The authors create examples to apply mathematical theory innovatively to measurement and control engineering. Not only does this reference provide theoretical knowledge, it provides information on first hand experiences.
Author: Santiago Aja-Fernández
Publisher: Springer
ISBN: 3319399349
Category : Computers
Languages : en
Pages : 338
Get Book Here
Book Description
This unique text presents a comprehensive review of methods for modeling signal and noise in magnetic resonance imaging (MRI), providing a systematic study, classifying and comparing the numerous and varied estimation and filtering techniques. Features: provides a complete framework for the modeling and analysis of noise in MRI, considering different modalities and acquisition techniques; describes noise and signal estimation for MRI from a statistical signal processing perspective; surveys the different methods to remove noise in MRI acquisitions from a practical point of view; reviews different techniques for estimating noise from MRI data in single- and multiple-coil systems for fully sampled acquisitions; examines the issue of noise estimation when accelerated acquisitions are considered, and parallel imaging methods are used to reconstruct the signal; includes appendices covering probability density functions, combinations of random variables used to derive estimators, and useful MRI datasets.
Author: Habib Ammari
Publisher: Springer
ISBN: 9783642229916
Category : Mathematics
Languages : en
Pages : 160
Get Book Here
Book Description
This volume reports on recent mathematical and computational advances in optical, ultrasound, and opto-acoustic tomographies. It outlines the state-of-the-art and future directions in these fields and provides readers with the most recently developed mathematical and computational tools. It is particularly suitable for researchers and graduate students in applied mathematics and biomedical engineering.
Author: Ke Chen
Publisher: Springer Nature
ISBN: 3030986616
Category : Mathematics
Languages : en
Pages : 1981
Get Book Here
Book Description
This handbook gathers together the state of the art on mathematical models and algorithms for imaging and vision. Its emphasis lies on rigorous mathematical methods, which represent the optimal solutions to a class of imaging and vision problems, and on effective algorithms, which are necessary for the methods to be translated to practical use in various applications. Viewing discrete images as data sampled from functional surfaces enables the use of advanced tools from calculus, functions and calculus of variations, and nonlinear optimization, and provides the basis of high-resolution imaging through geometry and variational models. Besides, optimization naturally connects traditional model-driven approaches to the emerging data-driven approaches of machine and deep learning. No other framework can provide comparable accuracy and precision to imaging and vision. Written by leading researchers in imaging and vision, the chapters in this handbook all start with gentle introductions, which make this work accessible to graduate students. For newcomers to the field, the book provides a comprehensive and fast-track introduction to the content, to save time and get on with tackling new and emerging challenges. For researchers, exposure to the state of the art of research works leads to an overall view of the entire field so as to guide new research directions and avoid pitfalls in moving the field forward and looking into the next decades of imaging and information services. This work can greatly benefit graduate students, researchers, and practitioners in imaging and vision; applied mathematicians; medical imagers; engineers; and computer scientists.
Author: Charles A. Bouman
Publisher: SIAM
ISBN: 1611977134
Category : Mathematics
Languages : en
Pages : 350
Get Book Here
Book Description
Collecting a set of classical and emerging methods previously unavailable in a single resource, Foundations of Computational Imaging: A Model-Based Approach is the first book to define a common foundation for the mathematical and statistical methods used in computational imaging. The book brings together a blend of research with applications in a variety of disciplines, including applied math, physics, chemistry, optics, and signal processing, to address a collection of problems that can benefit from a common set of methods. Readers will find basic techniques of model-based image processing, a comprehensive treatment of Bayesian and regularized image reconstruction methods, and an integrated treatment of advanced reconstruction techniques, such as majorization, constrained optimization, alternating direction method of multipliers (ADMM), and Plug-and-Play methods for model integration. Foundations of Computational Imaging can be used in courses on model-based or computational imaging, advanced numerical analysis, data science, numerical optimization, and approximation theory. It will also prove useful to researchers or practitioners in medical, scientific, commercial, and industrial imaging.
