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Computational Analysis And Modelling Of Graph Structured Neuroimaging Data
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Book Synopsis Computational Analysis and Modelling of Graph-structured Neuroimaging Data by : Ira Ktena
Download or read book Computational Analysis and Modelling of Graph-structured Neuroimaging Data written by Ira Ktena and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Computational and Network Modeling of Neuroimaging Data by : Kendrick Kay
Download or read book Computational and Network Modeling of Neuroimaging Data written by Kendrick Kay and published by Elsevier. This book was released on 2024-06-17 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neuroimaging is witnessing a massive increase in the quality and quantity of data being acquired. It is widely recognized that effective interpretation and extraction of information from such data requires quantitative modeling. However, modeling comes in many diverse forms, with different research communities tackling different brain systems, different spatial and temporal scales, and different aspects of brain structure and function. Computational and Network Modeling of Neuroimaging Data provides an authoritative and comprehensive overview of the many diverse modeling approaches that have been fruitfully applied to neuroimaging data. This book gives an accessible foundation to the field of computational and network modeling of neuroimaging data and is suitable for graduate students, academic researchers, and industry practitioners who are interested in adopting or applying model-based approaches in neuroimaging. Provides an authoritative and comprehensive overview of major modeling approaches to neuroimaging data Written by experts, the book's chapters use a common structure to introduce, motivate, and describe a specific modeling approach used in neuroimaging Gives insights into the similarities and differences across different modeling approaches Analyses details of outstanding research challenges in the field
Book Synopsis Exploratory Analysis and Data Modeling in Functional Neuroimaging by : Friedrich T. Sommer
Download or read book Exploratory Analysis and Data Modeling in Functional Neuroimaging written by Friedrich T. Sommer and published by MIT Press. This book was released on 2003 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: An overview of theoretical and computational approaches to neuroimaging.
Book Synopsis Statistical and Computational Methods in Brain Image Analysis by : Moo K. Chung
Download or read book Statistical and Computational Methods in Brain Image Analysis written by Moo K. Chung and published by CRC Press. This book was released on 2013-07-23 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 illustrations of actual imaging data and computer codes. Using MATLAB® and case study data sets, Statistical and Computational Methods in Brain Image Analysis is the first book to explicitly explain how to perform statistical analysis on brain imaging data. The book focuses on methodological issues in analyzing structural brain imaging modalities such as MRI and DTI. Real imaging applications and examples elucidate the concepts and methods. In addition, most of the brain imaging data sets and MATLAB codes are available on the author’s website. By supplying the data and codes, this book enables researchers to start their statistical analyses immediately. Also suitable for graduate students, it provides an understanding of the various statistical and computational methodologies used in the field as well as important and technically challenging topics.
Book Synopsis Handbook of Neuroimaging Data Analysis by : Hernando Ombao
Download or read book Handbook of Neuroimaging Data Analysis written by Hernando Ombao and published by CRC Press. This book was released on 2016-11-18 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 by : Anne L. Martel
Download or read book Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 written by Anne L. Martel and published by Springer Nature. This book was released on 2020-10-02 with total page 847 pages. Available in PDF, EPUB and Kindle. Book excerpt: The seven-volume set LNCS 12261, 12262, 12263, 12264, 12265, 12266, and 12267 constitutes the refereed proceedings of the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, held in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 542 revised full papers presented were carefully reviewed and selected from 1809 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: machine learning methodologies Part II: image reconstruction; prediction and diagnosis; cross-domain methods and reconstruction; domain adaptation; machine learning applications; generative adversarial networks Part III: CAI applications; image registration; instrumentation and surgical phase detection; navigation and visualization; ultrasound imaging; video image analysis Part IV: segmentation; shape models and landmark detection Part V: biological, optical, microscopic imaging; cell segmentation and stain normalization; histopathology image analysis; opthalmology Part VI: angiography and vessel analysis; breast imaging; colonoscopy; dermatology; fetal imaging; heart and lung imaging; musculoskeletal imaging Part VI: brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; positron emission tomography
Book Synopsis Computer Analysis of Images and Patterns by : Mario Vento
Download or read book Computer Analysis of Images and Patterns written by Mario Vento and published by Springer Nature. This book was released on 2019-08-22 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of two workshops held at the 18th International Conference on Computer Analysis of Images and Patterns, CAIP 2019, held in Salerno, Italy, in September 2019: First Workshop on Deep-learning based Computer Vision for UAV, DL-UAV 2019, and the First Workshop on Visual Computing and Machine Learning for Biomedical Applications, ViMaBi 2019. The 12 papers presented in this volume were carefully reviewed and selected from 16 submissions and focus on all aspects of visual computing and machine learning for biomedical applications, and deep-learning based computer vision for UAV.
Book Synopsis Machine Learning and Medical Imaging by : Guorong Wu
Download or read book Machine Learning and Medical Imaging written by Guorong Wu and published by Academic Press. This book was released on 2016-08-11 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/coding, and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs. The biomedical imaging modalities include ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), histology, and microscopy images. The targeted organs span the lung, liver, brain, and prostate, while there is also a treatment of examining genetic associations. Machine Learning and Medical Imaging is an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians. Demonstrates the application of cutting-edge machine learning techniques to medical imaging problems Covers an array of medical imaging applications including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics Features self-contained chapters with a thorough literature review Assesses the development of future machine learning techniques and the further application of existing techniques
Book Synopsis Medical Image Computing and Computer Assisted Intervention – MICCAI 2022 by : Linwei Wang
Download or read book Medical Image Computing and Computer Assisted Intervention – MICCAI 2022 written by Linwei Wang and published by Springer Nature. This book was released on 2022-09-15 with total page 774 pages. Available in PDF, EPUB and Kindle. Book excerpt: The eight-volume set LNCS 13431, 13432, 13433, 13434, 13435, 13436, 13437, and 13438 constitutes the refereed proceedings of the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022. The 574 revised full papers presented were carefully reviewed and selected from 1831 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: Brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; heart and lung imaging; dermatology; Part II: Computational (integrative) pathology; computational anatomy and physiology; ophthalmology; fetal imaging; Part III: Breast imaging; colonoscopy; computer aided diagnosis; Part IV: Microscopic image analysis; positron emission tomography; ultrasound imaging; video data analysis; image segmentation I; Part V: Image segmentation II; integration of imaging with non-imaging biomarkers; Part VI: Image registration; image reconstruction; Part VII: Image-Guided interventions and surgery; outcome and disease prediction; surgical data science; surgical planning and simulation; machine learning – domain adaptation and generalization; Part VIII: Machine learning – weakly-supervised learning; machine learning – model interpretation; machine learning – uncertainty; machine learning theory and methodologies.
Book Synopsis Proceedings of International Conference on Recent Innovations in Computing by : Yashwant Singh
Download or read book Proceedings of International Conference on Recent Innovations in Computing written by Yashwant Singh and published by Springer Nature. This book was released on 2023-05-02 with total page 668 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features selected papers presented at the 5th International Conference on Recent Innovations in Computing (ICRIC 2022), held on May 13–14, 2022, at the Central University of Jammu, India, and organized by the university’s Department of Computer Science and Information Technology. The conference was hosted in association with ELTE, Hungary; Knowledge University, Erbil; Cyber Security Research Lab and many other national & international partners. The book is divided into two volumes, and it includes the latest research in the areas of software engineering, cloud computing, computer networks and Internet technologies, artificial intelligence, information security, database and distributed computing, and digital India.
Book Synopsis Fundamentals of Brain Network Analysis by : Alex Fornito
Download or read book Fundamentals of Brain Network Analysis written by Alex Fornito and published by Academic Press. This book was released on 2016-03-04 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamentals of Brain Network Analysis is a comprehensive and accessible introduction to methods for unraveling the extraordinary complexity of neuronal connectivity. From the perspective of graph theory and network science, this book introduces, motivates and explains techniques for modeling brain networks as graphs of nodes connected by edges, and covers a diverse array of measures for quantifying their topological and spatial organization. It builds intuition for key concepts and methods by illustrating how they can be practically applied in diverse areas of neuroscience, ranging from the analysis of synaptic networks in the nematode worm to the characterization of large-scale human brain networks constructed with magnetic resonance imaging. This text is ideally suited to neuroscientists wanting to develop expertise in the rapidly developing field of neural connectomics, and to physical and computational scientists wanting to understand how these quantitative methods can be used to understand brain organization. Winner of the 2017 PROSE Award in Biomedicine & Neuroscience and the 2017 British Medical Association (BMA) Award in Neurology Extensively illustrated throughout by graphical representations of key mathematical concepts and their practical applications to analyses of nervous systems Comprehensively covers graph theoretical analyses of structural and functional brain networks, from microscopic to macroscopic scales, using examples based on a wide variety of experimental methods in neuroscience Designed to inform and empower scientists at all levels of experience, and from any specialist background, wanting to use modern methods of network science to understand the organization of the brain
Book Synopsis Statistical Parametric Mapping: The Analysis of Functional Brain Images by : William D. Penny
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
Book Synopsis Advanced Computational Intelligence Methods for Processing Brain Imaging Data by : Kaijian Xia
Download or read book Advanced Computational Intelligence Methods for Processing Brain Imaging Data written by Kaijian Xia and published by Frontiers Media SA. This book was released on 2022-11-09 with total page 754 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Bayesian Estimation and Inference in Computational Anatomy and Neuroimaging: Methods & Applications by : Xiaoying Tang
Download or read book Bayesian Estimation and Inference in Computational Anatomy and Neuroimaging: Methods & Applications written by Xiaoying Tang and published by Frontiers Media SA. This book was released on 2019-08-22 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Anatomy (CA) is an emerging discipline aiming to understand anatomy by utilizing a comprehensive set of mathematical tools. CA focuses on providing precise statistical encodings of anatomy with direct application to a broad range of biological and medical settings. During the past two decades, there has been an ever-increasing pace in the development of neuroimaging techniques, delivering in vivo information on the anatomy and physiological signals of different human organs through a variety of imaging modalities such as MRI, x-ray, CT, and PET. These multi-modality medical images provide valuable data for accurate interpretation and estimation of various biological parameters such as anatomical labels, disease types, cognitive states, functional connectivity between distinct anatomical regions, as well as activation responses to specific stimuli. In the era of big neuroimaging data, Bayes’ theorem provides a powerful tool to deliver statistical conclusions by combining the current information and prior experience. When sufficiently good data is available, Bayes’ theorem can utilize it fully and provide statistical inferences/estimations with the least error rate. Bayes’ theorem arose roughly three hundred years ago and has seen extensive application in many fields of science and technology, including recent neuroimaging, ever since. The last fifteen years have seen a great deal of success in the application of Bayes’ theorem to the field of CA and neuroimaging. That said, given that the power and success of Bayes’ rule largely depends on the validity of its probabilistic inputs, it is still a challenge to perform Bayesian estimation and inference on the typically noisy neuroimaging data of the real world. We assembled contributions focusing on recent developments in CA and neuroimaging through Bayesian estimation and inference, in terms of both methodologies and applications. It is anticipated that the articles in this Research Topic will provide a greater insight into the field of Bayesian imaging analysis.
Book Synopsis Graph Spectral Image Processing by : Gene Cheung
Download or read book Graph Spectral Image Processing written by Gene Cheung and published by John Wiley & Sons. This book was released on 2021-08-31 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graph spectral image processing is the study of imaging data from a graph frequency perspective. Modern image sensors capture a wide range of visual data including high spatial resolution/high bit-depth 2D images and videos, hyperspectral images, light field images and 3D point clouds. The field of graph signal processing – extending traditional Fourier analysis tools such as transforms and wavelets to handle data on irregular graph kernels – provides new flexible computational tools to analyze and process these varied types of imaging data. Recent methods combine graph signal processing ideas with deep neural network architectures for enhanced performances, with robustness and smaller memory requirements. The book is divided into two parts. The first is centered on the fundamentals of graph signal processing theories, including graph filtering, graph learning and graph neural networks. The second part details several imaging applications using graph signal processing tools, including image and video compression, 3D image compression, image restoration, point cloud processing, image segmentation and image classification, as well as the use of graph neural networks for image processing.
Book Synopsis Textbook of Autism Spectrum Disorders, Second Edition by : Eric Hollander, M.D.
Download or read book Textbook of Autism Spectrum Disorders, Second Edition written by Eric Hollander, M.D. and published by American Psychiatric Pub. This book was released on 2022-03-15 with total page 744 pages. Available in PDF, EPUB and Kindle. Book excerpt: More than 40 years after the official recognition of infantile autism in DSM-III, advances continue to be made in our understanding of the possible causes, assessment and evaluation, and treatment of autism spectrum disorder (ASD). With contributions by dozens of experts in the field, this second edition of the Textbook of Autism Spectrum Disorders has been updated to reflect the latest research in ASD. Unrivaled in its thoroughness, this volume discusses issues of assessment and evaluation; examines the etiology of ASD and its recognized associations with other medical conditions; analyzes standard and experimental treatments; and delves into social policy issues pertinent to individuals with ASD and those who treat them. With summary points in each chapter and copious lists of recommended readings, this is an indispensable resource for psychiatrists, psychologists, neurologists, social workers, speech therapists, educators, and all others in the continuum of care.
Book Synopsis Pattern Recognition and Computer Vision by : Huimin Ma
Download or read book Pattern Recognition and Computer Vision written by Huimin Ma and published by Springer Nature. This book was released on 2021-10-22 with total page 649 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 4-volume set LNCS 13019, 13020, 13021 and 13022 constitutes the refereed proceedings of the 4th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2021, held in Beijing, China, in October-November 2021. The 201 full papers presented were carefully reviewed and selected from 513 submissions. The papers have been organized in the following topical sections: Object Detection, Tracking and Recognition; Computer Vision, Theories and Applications, Multimedia Processing and Analysis; Low-level Vision and Image Processing; Biomedical Image Processing and Analysis; Machine Learning, Neural Network and Deep Learning, and New Advances in Visual Perception and Understanding.