Statistical And Computational Methods In Brain Image Analysis
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Statistical And Computational Methods In Brain Image Analysis
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Author : Moo K. Chung
language : en
Publisher: CRC Press
Release Date : 2013-07-23
Statistical And Computational Methods In Brain Image Analysis written by Moo K. Chung and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-23 with Mathematics categories.
The massive amount of nonstandard high-dimensional brain imaging data being generated is often difficult to analyze using current techniques. This challenge in brain image analysis requires new computational approaches and solutions. But none of the research papers or books in the field describe the quantitative techniques with detailed illustratio
Riemannian Geometric Statistics In Medical Image Analysis
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Author : Xavier Pennec
language : en
Publisher: Academic Press
Release Date : 2019-09-04
Riemannian Geometric Statistics In Medical Image Analysis written by Xavier Pennec and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-04 with Computers categories.
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.
Handbook Of Neuroimaging Data Analysis
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Author : Hernando Ombao
language : en
Publisher: CRC Press
Release Date : 2016-11-18
Handbook Of Neuroimaging Data Analysis written by Hernando Ombao and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-18 with Mathematics categories.
This book explores various state-of-the-art aspects behind the statistical analysis of neuroimaging data. It examines the development of novel statistical approaches to model brain data. Designed for researchers in statistics, biostatistics, computer science, cognitive science, computer engineering, biomedical engineering, applied mathematics, physics, and radiology, the book can also be used as a textbook for graduate-level courses in statistics and biostatistics or as a self-study reference for Ph.D. students in statistics, biostatistics, psychology, neuroscience, and computer science.
Statistical Methods In Psychiatry And Related Fields
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Author : Ralitza Gueorguieva
language : en
Publisher: CRC Press
Release Date : 2017-11-20
Statistical Methods In Psychiatry And Related Fields written by Ralitza Gueorguieva and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-20 with Mathematics categories.
Data collected in psychiatry and related fields are complex because outcomes are rarely directly observed, there are multiple correlated repeated measures within individuals, there is natural heterogeneity in treatment responses and in other characteristics in the populations. Simple statistical methods do not work well with such data. More advanced statistical methods capture the data complexity better, but are difficult to apply appropriately and correctly by investigators who do not have advanced training in statistics. This book presents, at a non-technical level, several approaches for the analysis of correlated data: mixed models for continuous and categorical outcomes, nonparametric methods for repeated measures and growth mixture models for heterogeneous trajectories over time. Separate chapters are devoted to techniques for multiple comparison correction, analysis in the presence of missing data, adjustment for covariates, assessment of mediator and moderator effects, study design and sample size considerations. The focus is on the assumptions of each method, applicability and interpretation rather than on technical details. Features Provides an overview of intermediate to advanced statistical methods applied to psychiatry. Takes a non-technical approach with mathematical details kept to a minimum. Includes lots of detailed examples from published studies in psychiatry and related fields. Software programs, data sets and output are available on a supplementary website. The intended audience are applied researchers with minimal knowledge of statistics, although the book could also benefit collaborating statisticians. The book, together with the online materials, is a valuable resource aimed at promoting the use of appropriate statistical methods for the analysis of repeated measures data. Ralitza Gueorguieva is a Senior Research Scientist at the Department of Biostatistics, Yale School of Public Health. She has more than 20 years experience in statistical methodology development and collaborations with psychiatrists and other researchers, and is the author of over 130 peer-reviewed publications.
Spatial Statistics And Computational Methods
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Author : Jesper Møller
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17
Spatial Statistics And Computational Methods written by Jesper Møller and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-17 with Mathematics categories.
Spatial statistics and Markov Chain Monte Carlo (MCMC) techniques have each undergone major developments in the last decade. Also, these two areas are mutually reinforcing, because MCMC methods are often necessary for the practical implementation of spatial statistical inference, while new spatial stochastic models in turn motivate the development of improved MCMC algorithms. This volume shows how sophisticated spatial statistical and computational methods apply to a range of problems of increasing importance for applications in science and technology. It consists of four chapters: 1. Petros Dellaportas and Gareth O. Roberts give a tutorial on MCMC methods, the computational methodology which is essential for virtually all the complex spatial models to be considered in subsequent chapters. 2. Peter J. Diggle, Paulo J, Ribeiro Jr., and Ole F. Christensen introduce the reader to the model- based approach to geostatistics, i.e. the application of general statistical principles to the formulation of explicit stochastic models for geostatistical data, and to inference within a declared class of models. 3. Merrilee A. Hurn, Oddvar K. Husby, and H?vard Rue discuss various aspects of image analysis, ranging from low to high level tasks, and illustrated with different examples of applications. 4. Jesper Moller and Rasmus P. Waggepetersen collect recent theoretical advances in simulation-based inference for spatial point processes, and discuss some examples of applications. The volume introduces topics of current interest in spatial and computational statistics, which should be accessible to postgraduate students as well as to experienced statistical researchers. It is partly based on the course material for the "TMR and MaPhySto Summer School on Spatial Statistics and Computational Methods," held at Aalborg University, Denmark, August 19-22, 2001.
Variational Methods In Image Processing
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Author : Luminita A. Vese
language : en
Publisher: CRC Press
Release Date : 2015-11-18
Variational Methods In Image Processing written by Luminita A. Vese and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-18 with Computers categories.
Variational Methods in Image Processing presents the principles, techniques, and applications of variational image processing. The text focuses on variational models, their corresponding Euler–Lagrange equations, and numerical implementations for image processing. It balances traditional computational models with more modern techniques that solve the latest challenges introduced by new image acquisition devices. The book addresses the most important problems in image processing along with other related problems and applications. Each chapter presents the problem, discusses its mathematical formulation as a minimization problem, analyzes its mathematical well-posedness, derives the associated Euler–Lagrange equations, describes the numerical approximations and algorithms, explains several numerical results, and includes a list of exercises. MATLAB® codes are available online. Filled with tables, illustrations, and algorithms, this self-contained textbook is primarily for advanced undergraduate and graduate students in applied mathematics, scientific computing, medical imaging, computer vision, computer science, and engineering. It also offers a detailed overview of the relevant variational models for engineers, professionals from academia, and those in the image processing industry.
Medical Imaging Systems Technology Volume 1 Analysis And Computational Methods
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Author : Cornelius T Leondes
language : en
Publisher: World Scientific
Release Date : 2005-08-25
Medical Imaging Systems Technology Volume 1 Analysis And Computational Methods written by Cornelius T Leondes and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-08-25 with Medical categories.
This scholarly set of well-harmonized volumes provides indispensable and complete coverage of the exciting and evolving subject of medical imaging systems. Leading experts on the international scene tackle the latest cutting-edge techniques and technologies in an in-depth but eminently clear and readable approach.Complementing and intersecting one another, each volume offers a comprehensive treatment of substantive importance to the subject areas. The chapters, in turn, address topics in a self-contained manner with authoritative introductions, useful summaries, and detailed reference lists. Extensively well-illustrated with figures throughout, the five volumes as a whole achieve a unique depth and breath of coverage.As a cohesive whole or independent of one another, the volumes may be acquired as a set or individually.
An Image Processing Tour Of College Mathematics
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Author : Yevgeniy V. Galperin
language : en
Publisher: CRC Press
Release Date : 2021-02-10
An Image Processing Tour Of College Mathematics written by Yevgeniy V. Galperin and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-10 with Computers categories.
An Image Processing Tour of College Mathematics aims to provide meaningful context for reviewing key topics of the college mathematics curriculum, to help students gain confidence in using concepts and techniques of applied mathematics, to increase student awareness of recent developments in mathematical sciences, and to help students prepare for graduate studies. The topics covered include a library of elementary functions, basic concepts of descriptive statistics, probability distributions of functions of random variables, definitions and concepts behind first- and second-order derivatives, most concepts and techniques of traditional linear algebra courses, an introduction to Fourier analysis, and a variety of discrete wavelet transforms – all of that in the context of digital image processing. Features Pre-calculus material and basic concepts of descriptive statistics are reviewed in the context of image processing in the spatial domain. Key concepts of linear algebra are reviewed both in the context of fundamental operations with digital images and in the more advanced context of discrete wavelet transforms. Some of the key concepts of probability theory are reviewed in the context of image equalization and histogram matching. The convolution operation is introduced painlessly and naturally in the context of naïve filtering for denoising and is subsequently used for edge detection and image restoration. An accessible elementary introduction to Fourier analysis is provided in the context of image restoration. Discrete wavelet transforms are introduced in the context of image compression, and the readers become more aware of some of the recent developments in applied mathematics. This text helps students of mathematics ease their way into mastering the basics of scientific computer programming.
Computational Methods In Biophysics Biomaterials Biotechnology And Medical Systems
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Author : Cornelius T. Leondes
language : en
Publisher: Springer Nature
Release Date : 2006-09-21
Computational Methods In Biophysics Biomaterials Biotechnology And Medical Systems written by Cornelius T. Leondes and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-09-21 with Technology & Engineering categories.
The cross-disciplinary pursuits between modern technology, their computations and applications to the human body have exploded because of rapid developments in computer technology and mathematical computational techniques. This four-volume set, Computational Methods in Biophysics, Biomaterials, Biotechnology and Medical Systems, represents the first multi-volume treatment of this significant subject on the international scene. The work is an indispensable reference source by leading researchers, and is essential reference work for academics, practitioners, students and researchers working with: *Computers in Medicine, *Science and Mathematics in Biomaterials, Biomechanics and Bioengineering, *Computational Biophysics.
Statistical Parametric Mapping The Analysis Of Functional Brain Images
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Author : William D. Penny
language : en
Publisher: Elsevier
Release Date : 2011-04-28
Statistical Parametric Mapping The Analysis Of Functional Brain Images written by William D. Penny and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-28 with Psychology categories.
In an age where the amount of data collected from brain imaging is increasing constantly, it is of critical importance to analyse those data within an accepted framework to ensure proper integration and comparison of the information collected. This book describes the ideas and procedures that underlie the analysis of signals produced by the brain. The aim is to understand how the brain works, in terms of its functional architecture and dynamics. This book provides the background and methodology for the analysis of all types of brain imaging data, from functional magnetic resonance imaging to magnetoencephalography. Critically, Statistical Parametric Mapping provides a widely accepted conceptual framework which allows treatment of all these different modalities. This rests on an understanding of the brain's functional anatomy and the way that measured signals are caused experimentally. The book takes the reader from the basic concepts underlying the analysis of neuroimaging data to cutting edge approaches that would be difficult to find in any other source. Critically, the material is presented in an incremental way so that the reader can understand the precedents for each new development. This book will be particularly useful to neuroscientists engaged in any form of brain mapping; who have to contend with the real-world problems of data analysis and understanding the techniques they are using. It is primarily a scientific treatment and a didactic introduction to the analysis of brain imaging data. It can be used as both a textbook for students and scientists starting to use the techniques, as well as a reference for practicing neuroscientists. The book also serves as a companion to the software packages that have been developed for brain imaging data analysis. - An essential reference and companion for users of the SPM software - Provides a complete description of the concepts and procedures entailed by the analysis of brain images - Offers full didactic treatment of the basic mathematics behind the analysis of brain imaging data - Stands as a compendium of all the advances in neuroimaging data analysis over the past decade - Adopts an easy to understand and incremental approach that takes the reader from basic statistics to state of the art approaches such as Variational Bayes - Structured treatment of data analysis issues that links different modalities and models - Includes a series of appendices and tutorial-style chapters that makes even the most sophisticated approaches accessible