Download or read book Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy written by Dajiang Zhu and published by Springer Nature. This book was released on 2019-10-10 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed joint proceedings of the 4th International Workshop on Multimodal Brain Image Analysis, MBAI 2019, and the 7th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019. The 16 full papers presented at MBAI 2019 and the 7 full papers presented at MFCA 2019 were carefully reviewed and selected. The MBAI papers intend to move forward the state of the art in multimodal brain image analysis, in terms of analysis methodologies, algorithms, software systems, validation approaches, benchmark datasets, neuroscience, and clinical applications. The MFCA papers are devoted to statistical and geometrical methods for modeling the variability of biological shapes. The goal is to foster the interactions between the mathematical community around shapes and the MICCAI community around computational anatomy applications.

Download or read book Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging written by Ke Chen and published by Springer Nature. This book was released on 2023-02-24 with total page 1981 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Medical Image Computing and Computer Assisted Intervention MICCAI 2024 written by Marius George Linguraru and published by Springer Nature. This book was released on with total page 819 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Intelligent Analysis of Biomedical Imaging Data for Precision Medicine written by Kuanquan Wang and published by Frontiers Media SA. This book was released on 2022-11-09 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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 510 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. - Presents an accessible introduction to the basic concepts, methods, algorithms and techniques in statistical shape and deformation analysis - Includes implementation examples using open source software - Covers real-life applications of statistical shape and deformation analysis methods

Download or read book Advanced Machine Learning Approaches for Brain Mapping written by Dajiang Zhu and published by Frontiers Media SA. This book was released on 2024-04-10 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brain mapping is dedicated to using brain imaging techniques such as MRI, CT, PET, EEG, and fNIRS to understand the brain anatomy, structure, and function, and how it contributes to cognition, behavior, and deficits of brain diseases. Recently, machine learning is in a stage of rapid development, and various new technologies are continuously introduced into the field, from traditional approaches

Download or read book Multimodal Brain Image Analysis written by Li Shen and published by Springer. This book was released on 2013-08-15 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Workshop on Multimodal Brain Image Analysis, MBIA 2013, held in Nagoya, Japan, on September 22, 2013 in conjunction with the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI. The 24 revised full papers presented were carefully reviewed and selected from 35 submissions. The papers are organized in topical sections on analysis, methodologies, algorithms, software systems, validation approaches, benchmark datasets, neuroscience and clinical applications.

Download or read book Statistical Parametric Mapping The Analysis of Functional Brain Images written by William D. Penny and published by Elsevier. This book was released on 2011-04-28 with total page 689 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Brain Mapping The Disorders written by John C. Mazziotta and published by Elsevier. This book was released on 2000-05-24 with total page 691 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brain Mapping: The Disorders is the first comprehensive text to describe the uses of the latest brain mapping technologies in the evaluation of patients with neurological, neurosurgical and psychiatric disorders. With contributions from the leading figures in the field, this heavily illustrated text is organized by disorders of brain systems, with specific examples of how one should use current neuroimaging techniques to evaluate patients with specific cerebral disorders. Comprehensive in scope, the text discusses patient evaluations using the wide range of modern magnetic resonance imaging techniques, positron emission tomography, single photon emission computed tomography, optical intrinsic signal imaging, electroencephalography, magnetoencephalography, and transcranial magnetic stimulation. The third in this brain mapping series, Brain Mapping: The Disorders, is the ultimate text for anyone interested in the use of brain mapping techniques to study patients with disorders of the central nervous system. - Provides a comprehensive, in-depth view of the current brain mapping techniques as they are used in the evaluation of patients with cerebral disorders - Heavily illustrated to provide actual examples of the use of the specific techniques - Includes contributions from the leaders in the field ensure authoritative and up-to-date material - Completes the trilogy of three brain mapping texts dealing, respectively, with the methods, the applications of these methods in the normal brain and in patients with neurological, neurosurgical, and psychiatric disorders

Download or read book Riemannian Geometric Statistics in Medical Image Analysis written by Xavier Pennec and published by Academic Press. This book was released on 2019-09-02 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Medical Image Computing and Computer Assisted Intervention MICCAI 2012 written by Nicholas Ayache and published by Springer. This book was released on 2012-08-28 with total page 645 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 7510, 7511, and 7512 constitutes the refereed proceedings of the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012, held in Nice, France, in October 2012. Based on rigorous peer reviews, the program committee carefully selected 252 revised papers from 781 submissions for presentation in three volumes. The third volume includes 79 papers organized in topical sections on diffusion imaging: from acquisition to tractography; image acquisition, segmentation and recognition; image registration; neuroimage analysis; analysis of microscopic and optical images; image segmentation; diffusion weighted imaging; computer-aided diagnosis and planning; and microscopic image analysis.

Download or read book Handbook of Mathematical Methods in Imaging written by Otmar Scherzer and published by Springer Science & Business Media. This book was released on 2010-11-23 with total page 1626 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Mathematical Methods in Imaging provides a comprehensive treatment of the mathematical techniques used in imaging science. The material is grouped into two central themes, namely, Inverse Problems (Algorithmic Reconstruction) and Signal and Image Processing. Each section within the themes covers applications (modeling), mathematics, numerical methods (using a case example) and open questions. Written by experts in the area, the presentation is mathematically rigorous. The entries are cross-referenced for easy navigation through connected topics. Available in both print and electronic forms, the handbook is enhanced by more than 150 illustrations and an extended bibliography. It will benefit students, scientists and researchers in applied mathematics. Engineers and computer scientists working in imaging will also find this handbook useful.

Download or read book Information Processing in Medical Imaging written by Albert C. S. Chung and published by Springer. This book was released on 2019-05-22 with total page 888 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 26th International Conference on Information Processing in Medical Imaging, IPMI 2019, held at the Hong Kong University of Science and Technology, Hong Kong, China, in June 2019. The 69 full papers presented in this volume were carefully reviewed and selected from 229 submissions. They were organized in topical sections on deep learning and segmentation; classification and inference; reconstruction; disease modeling; shape, registration; learning motion; functional imaging; and white matter imaging. The book also includes a number of post papers.

Download or read book Medical Imaging Informatics written by Alex A.T. Bui and published by Springer Science & Business Media. This book was released on 2009-12-01 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Medical Imaging Informatics provides an overview of this growing discipline, which stems from an intersection of biomedical informatics, medical imaging, computer science and medicine. Supporting two complementary views, this volume explores the fundamental technologies and algorithms that comprise this field, as well as the application of medical imaging informatics to subsequently improve healthcare research. Clearly written in a four part structure, this introduction follows natural healthcare processes, illustrating the roles of data collection and standardization, context extraction and modeling, and medical decision making tools and applications. Medical Imaging Informatics identifies core concepts within the field, explores research challenges that drive development, and includes current state-of-the-art methods and strategies.

Download or read book Pattern Recognition and Machine Learning written by Christopher M. Bishop and published by Springer. This book was released on 2016-08-23 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

Download or read book Quantitative Magnetic Resonance Imaging written by Nicole Seiberlich and published by Academic Press. This book was released on 2020-11-18 with total page 1094 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantitative Magnetic Resonance Imaging is a 'go-to' reference for methods and applications of quantitative magnetic resonance imaging, with specific sections on Relaxometry, Perfusion, and Diffusion. Each section will start with an explanation of the basic techniques for mapping the tissue property in question, including a description of the challenges that arise when using these basic approaches. For properties which can be measured in multiple ways, each of these basic methods will be described in separate chapters. Following the basics, a chapter in each section presents more advanced and recently proposed techniques for quantitative tissue property mapping, with a concluding chapter on clinical applications. The reader will learn: - The basic physics behind tissue property mapping - How to implement basic pulse sequences for the quantitative measurement of tissue properties - The strengths and limitations to the basic and more rapid methods for mapping the magnetic relaxation properties T1, T2, and T2* - The pros and cons for different approaches to mapping perfusion - The methods of Diffusion-weighted imaging and how this approach can be used to generate diffusion tensor - maps and more complex representations of diffusion - How flow, magneto-electric tissue property, fat fraction, exchange, elastography, and temperature mapping are performed - How fast imaging approaches including parallel imaging, compressed sensing, and Magnetic Resonance - Fingerprinting can be used to accelerate or improve tissue property mapping schemes - How tissue property mapping is used clinically in different organs - Structured to cater for MRI researchers and graduate students with a wide variety of backgrounds - Explains basic methods for quantitatively measuring tissue properties with MRI - including T1, T2, perfusion, diffusion, fat and iron fraction, elastography, flow, susceptibility - enabling the implementation of pulse sequences to perform measurements - Shows the limitations of the techniques and explains the challenges to the clinical adoption of these traditional methods, presenting the latest research in rapid quantitative imaging which has the possibility to tackle these challenges - Each section contains a chapter explaining the basics of novel ideas for quantitative mapping, such as compressed sensing and Magnetic Resonance Fingerprinting-based approaches

Download or read book Medical Image Registration written by Joseph V. Hajnal and published by CRC Press. This book was released on 2001-06-27 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image registration is the process of systematically placing separate images in a common frame of reference so that the information they contain can be optimally integrated or compared. This is becoming the central tool for image analysis, understanding, and visualization in both medical and scientific applications. Medical Image Registration provid