Methods For Analyzing Large Neuroimaging Datasets

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Methods For Analyzing Large Neuroimaging Datasets

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Author : Robert Whelan
language : en
Publisher: Springer Nature
Release Date : 2024-12-09

Methods For Analyzing Large Neuroimaging Datasets written by Robert Whelan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-09 with Science categories.

This Open Access volume explores the latest advancements and challenges in standardized methodologies, efficient code management, and scalable data processing of neuroimaging datasets. The chapters in this book are organized in four parts. Part One shows the researcher how to access and download large datasets, and how to compute at scale. Part Two covers best practices for working with large data, including how to build reproducible pipelines and how to use Git. Part Three looks at how to do structural and functional preprocessing data at scale, and Part Four describes various toolboxes for interrogating large neuroimaging datasets, including machine learning and deep learning approaches. In the Neuromethods series style, chapters include the kind of detail and key advice from the specialists needed to get successful results in your laboratory. Authoritative and comprehensive, Methods for Analyzing Large Neuroimaging Datasets is a valuable resource that will help researchers obtain the practical knowledge necessary for conducting robust and reproducible analyses of large neuroimaging datasets.

Big Data In Psychiatry And Neurology

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Author : Ahmed Moustafa
language : en
Publisher: Academic Press
Release Date : 2021-06-11

Big Data In Psychiatry And Neurology written by Ahmed Moustafa and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-11 with Medical categories.

Big Data in Psychiatry and Neurology provides an up-to-date overview of achievements in the field of big data in Psychiatry and Medicine, including applications of big data methods to aging disorders (e.g., Alzheimer's disease and Parkinson's disease), mood disorders (e.g., major depressive disorder), and drug addiction. This book will help researchers, students and clinicians implement new methods for collecting big datasets from various patient populations. Further, it will demonstrate how to use several algorithms and machine learning methods to analyze big datasets, thus providing individualized treatment for psychiatric and neurological patients. As big data analytics is gaining traction in psychiatric research, it is an essential component in providing predictive models for both clinical practice and public health systems. As compared with traditional statistical methods that provide primarily average group-level results, big data analytics allows predictions and stratification of clinical outcomes at an individual subject level. - Discusses longitudinal big data and risk factors surrounding the development of psychiatric disorders - Analyzes methods in using big data to treat psychiatric and neurological disorders - Describes the role machine learning can play in the analysis of big data - Demonstrates the various methods of gathering big data in medicine - Reviews how to apply big data to genetics

Adversarial Deep Generative Techniques For Early Diagnosis Of Neurological Conditions And Mental Health Practises

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Author : Abhishek Kumar
language : en
Publisher: Springer Nature
Release Date : 2025-08-16

Adversarial Deep Generative Techniques For Early Diagnosis Of Neurological Conditions And Mental Health Practises written by Abhishek Kumar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-16 with Computers categories.

This book explores a pioneering exploration of how deep generative models, including generative adversarial networks (GANs) and variational autoencoders (VAEs), renovating early neurological disorder detection. This book is a bridge between computational neuroscience and clinical neurology gaps, providing novel AI-driven methodologies for diagnosing conditions such as Alzheimer’s, Parkinson’s, epilepsy, and neurodevelopmental disorders. With a strong focus on neuroimaging, genomic data analysis, and biomedical informatics, the book equips researchers and practitioners with the tools to improve diagnostic accuracy and decision-making. It includes practical case studies, visual illustrations, and structured methodologies for training and validating deep learning models. Designed for neurologists, radiologists, data scientists, and AI researchers, this book is an essential resource for advancing precision medicine and next-generation healthcare innovation.

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

Machine Learning And Medical Imaging

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Author : Guorong Wu
language : en
Publisher: Academic Press
Release Date : 2016-08-11

Machine Learning And Medical Imaging written by Guorong Wu and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-11 with Computers categories.

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

Fmri Techniques And Protocols

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Author : Massimo Filippi
language : en
Publisher: Springer Nature
Release Date : 2025-06-02

Fmri Techniques And Protocols written by Massimo Filippi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-02 with Science categories.

This third edition volume expands on the previous edition with updates on the latest methodological aspects of fMRI and achievements made through the applications to the study of central nervous system functioning in the clinical field. The chapters in the book are organized in four parts: Part One talks about the basic knowledge for the understanding of the technical aspects of fMRI. Part Two describes the main findings obtained from the application of fMRI to study brain system function of healthy individuals. Part Three explores clinical findings obtained from the use of fMRI to assess the role of brain plasticity in major neurological and psychiatric conditions. Part Four presents novel approaches for the integration of fMRI data with measures of damage assessed using structural MR techniques and the use of fMRI to image spinal cord function. In the Neuromethods series style, chapters include the kind of detail and key advice from the specialists needed to get successful results in your laboratory. Cutting-edge and comprehensive, fMRI Techniques and Protocols, Third Edition provides clinicians and researchers with a “user-friendly” summary of the field, and helps them plan and carry out successful studies.

Big Data In Multimodal Medical Imaging

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Author : Ayman El-Baz
language : en
Publisher: CRC Press
Release Date : 2019-11-05

Big Data In Multimodal Medical Imaging written by Ayman El-Baz and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-05 with Computers categories.

There is an urgent need to develop and integrate new statistical, mathematical, visualization, and computational models with the ability to analyze Big Data in order to retrieve useful information to aid clinicians in accurately diagnosing and treating patients. The main focus of this book is to review and summarize state-of-the-art big data and deep learning approaches to analyze and integrate multiple data types for the creation of a decision matrix to aid clinicians in the early diagnosis and identification of high risk patients for human diseases and disorders. Leading researchers will contribute original research book chapters analyzing efforts to solve these important problems.

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.

Transforming Neuropsychology And Cognitive Psychology With Ai And Machine Learning

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Author : Bansal, Rohit
language : en
Publisher: IGI Global
Release Date : 2025-01-03

Transforming Neuropsychology And Cognitive Psychology With Ai And Machine Learning written by Bansal, Rohit and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-03 with Psychology categories.

The integration of artificial intelligence and machine learning into neuropsychology and cognitive psychology is revolutionizing how we understand, diagnose, and treat neurological and psychological conditions. By leveraging advanced algorithms, these technologies enable earlier detection of cognitive decline, more precise diagnoses, and personalized therapeutic interventions. They enhance the accuracy of neuropsychological assessments, automate scoring processes, and uncover subtle patterns in data that traditional methods might overlook. Furthermore, real-time data analysis from wearable devices and smartphones offers a continuous understanding of cognitive and emotional states, bridging the gap between clinical settings and daily life. This convergence promises to transform patient care and advance research, paving the way for more effective and innovative solutions in mental health and brain science. Transforming Neuropsychology and Cognitive Psychology With AI and Machine Learning highlights the synergies between neuropsychology, cognitive psychology, AI, and machine learning, and explores innovative applications, methodologies, and future prospects. It serves as a comprehensive resource for the latest advancements in AI algorithms and machine learning within neuropsychology and cognitive psychology. Covering topics such as AI-driven assessments, college counseling, and virtual reality, this book is an excellent resource for academicians, researchers, graduate and postgraduate students, mental health practitioners, industry researchers, non-governmental and governmental organizations, and more.

Computational Methods For Translational Brain Behavior Analysis

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Author : Rong Chen
language : en
Publisher: Frontiers Media SA
Release Date : 2021-06-24

Computational Methods For Translational Brain Behavior Analysis written by Rong Chen and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-24 with Science categories.