Learning Neuroimaging
Learning Neuroimaging

Author: Francisco de Asís Bravo-Rodríguez

Publisher: Springer Science & Business Media

Published: 2011-10-26

Total Pages: 239

ISBN-13: 3642229999

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This book is intended as an introduction to neuroradiology and aims to provide the reader with a comprehensive overview of this highly specialized radiological subspecialty. One hundred illustrated cases from clinical practice are presented in a standard way. Each case is supported by representative images and is divided into three parts: a brief summary of the patient’s medical history, a discussion of the disease, and a description of the most characteristic imaging features of the disorder. The focus is not only on common neuroradiological entities such as stroke and acute head trauma but also on less frequent disorders that the practitioner should recognize. Learning Neuroimaging: 100 Essential Cases is an ideal resource for neuroradiology and radiology residents, neurology residents, neurosurgery residents, nurses, radiology technicians, and medical students.

Machine Learning in Clinical Neuroimaging
Machine Learning in Clinical Neuroimaging

Author: Ahmed Abdulkadir

Publisher: Springer Nature

Published: 2021-09-22

Total Pages: 185

ISBN-13: 3030875865

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This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2021, held on September 27, 2021, in conjunction with MICCAI 2021. The workshop was held virtually due to the COVID-19 pandemic. The 17 papers presented in this book were carefully reviewed and selected from 27 submissions. They were organized in topical sections named: computational anatomy and brain networks and time series.

Neuroimaging Personality, Social Cognition, and Character
Neuroimaging Personality, Social Cognition, and Character

Author: John R Absher

Publisher: Academic Press

Published: 2016-01-30

Total Pages: 422

ISBN-13: 0128011661

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Neuroimaging Personality, Social Cognition, and Character covers the science of combining brain imaging with other analytical techniques for use in understanding cognition, behavior, consciousness, memory, language, visual perception, emotional control, and other human attributes. Multidimensional brain imaging research has led to a greater understanding of character traits such as honesty, generosity, truthfulness, and foresight previously unachieved by quantitative mapping. This book summarizes the latest brain imaging research pertaining to character with structural and functional human brain imaging in both normal individuals and those with brain disease or disorder, including psychiatric disorders.By reviewing and synthesizing the latest structural and functional brain imaging research related to character, this book situates itself into the larger framework of cognitive neuroscience, psychiatric neuroimaging, related fields of research, and a wide range of academic fields, such as politics, psychology, medicine, education, law, and religion. Provides a novel innovative reference on the emerging use of neuroimaging to reveal the biological substrates of character, such as optimism, honesty, generosity, and others Features chapters from leading physicians and researchers in the field Contains full-color text that includes both an overview of multiple disciplines and a detailed review of modern neuroimaging tools as they are applied to study human character Presents an integrative volume with far-reaching implications for guiding future imaging research in the social, psychological and medical sciences, and for applying these findings to a wide range of non-clinical disciplines such as law, politics, and religion Connects brain structure and function to human character and integrates modern neuroimaging techniques and other research methods for this purpose

Introduction to Neuroimaging Analysis
Introduction to Neuroimaging Analysis

Author: Mark Jenkinson

Publisher: Oxford University Press

Published: 2018

Total Pages: 277

ISBN-13: 0198816308

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This accessible primer gives an introduction to the wide array of MRI-based neuroimaging methods that are used in research. It provides an overview of the fundamentals of what different MRI modalities measure, what artifacts commonly occur, the essentials of the analysis, and common 'pipelines'.

Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology
Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology

Author: Seyed Mostafa Kia

Publisher: Springer Nature

Published: 2020-12-30

Total Pages: 319

ISBN-13: 3030668436

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This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2020, and the Second International Workshop on Radiogenomics in Neuro-oncology, RNO-AI 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020.* For MLCN 2020, 18 papers out of 28 submissions were accepted for publication. The accepted papers present novel contributions in both developing new machine learning methods and applications of existing methods to solve challenging problems in clinical neuroimaging. For RNO-AI 2020, all 8 submissions were accepted for publication. They focus on addressing the problems of applying machine learning to large and multi-site clinical neuroimaging datasets. The workshop aimed to bring together experts in both machine learning and clinical neuroimaging to discuss and hopefully bridge the existing challenges of applied machine learning in clinical neuroscience. *The workshops were held virtually due to the COVID-19 pandemic.

Machine Learning and Other Artificial Intelligence Applications, An Issue of Neuroimaging Clinics of North America, E-Book
Machine Learning and Other Artificial Intelligence Applications, An Issue of Neuroimaging Clinics of North America, E-Book

Author: Reza Forghani

Publisher: Elsevier Health Sciences

Published: 2020-10-23

Total Pages: 192

ISBN-13: 0323712452

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This issue of Neuroimaging Clinics of North America focuses on Artificial Intelligence and Machine Learning and is edited by Dr. Reza Forghani. Articles will include: A Brief History of Artificial Intelligence; Evolution of Approaches for Computerized Image Analysis; Overview of Machine Learning Part 1: Classic Approaches; Overview of Machine Learning Part 2: Artificial Neural Networks & Deep Learning; Overview of Natural Language Processing; Artificial Intelligence & Stroke Imaging: An East Coast Perspective; Artificial Intelligence & Stroke Imaging: A West Coast Perspective; Artificial Intelligence Applications for Brain Tumor Imaging; Diverse Applications of Artificial Intelligence in Neuroradiology; Artificial Intelligence Applications for Head and Neck Imaging; Artificial Intelligence Applications for Predictive Analytics and Workflow Optimization; Artificial Intelligence, Advanced Visualization, and 3D Printing; Ethical & Legal Considerations for Artificial Intelligence; Comprehensive (or 360) Artificial Intelligence: Beyond Image Interpretation Alone, and more!

Oxford Textbook of Neuroimaging
Oxford Textbook of Neuroimaging

Author: Massimo Filippi

Publisher: Oxford Textbooks in Clinical N

Published: 2015

Total Pages: 433

ISBN-13: 0199664099

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Part of the Oxford Textbooks in Clinical Neurology series, the Oxford Textbook of Neuroimaging provides an overview of the established and latest neuroimaging methodologies, and illustrates their application to the main diseases of the brain and the spinal cord including movement disorders, headache and stroke. In addition, assessments of neuroimaging techniques in both adult and paediatric neurological conditions are included, enabling thorough examples from both age groups. This full-colour book contains 280 detailed photographs and illustrations that enable a clear understanding of each technique. Covering the newest advances, each different imagining technique is comprehensively described, providing a practical relevance and a stimulus for more in-depth readings. The print edition is supplemented with a concurrent online edition, which allows access to the full content of the textbook, contains links from the references to primary research journal articles, and provides access to figures and tables that can be downloaded by the user. Providing a balanced state-of-the-art guide to neuroimaging for neurologists and radiologists, this title will enhance understanding of the pathophysiological basis of neurological conditions and will help set the stage for future research.

Machine Learning and Interpretation in Neuroimaging
Machine Learning and Interpretation in Neuroimaging

Author: Georg Langs

Publisher: Springer

Published: 2012-11-11

Total Pages: 277

ISBN-13: 3642347134

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Brain imaging brings together the technology, methodology, research questions and approaches of a wide range of scientific fields including physics, statistics, computer science, neuroscience, biology, and engineering. Thus, methodological and technological advances that enable us to obtain measurements, examine relationships across observations, and link these data to neuroscientific hypotheses happen in a highly interdisciplinary environment. The dynamic field of machine learning with its modern approach to data mining provides many relevant approaches for neuroscience and enables the exploration of open questions. This state-of-the-art survey offers a collection of papers from the Workshop on Machine Learning and Interpretation in Neuroimaging, MLINI 2011, held at the 25th Annual Conference on Neural Information Processing, NIPS 2011, in the Sierra Nevada, Spain, in December 2011. Additionally, invited speakers agreed to contribute reviews on various aspects of the field, adding breadth and perspective to the volume. The 32 revised papers were carefully selected from 48 submissions. At the interface between machine learning and neuroimaging the papers aim at shedding some light on the state of the art in this interdisciplinary field. They are organized in topical sections on coding and decoding, neuroscience, dynamcis, connectivity, and probabilistic models and machine learning.

Data Science for Neuroimaging
Data Science for Neuroimaging

Author: Ariel Rokem

Publisher: Princeton University Press

Published: 2023-11-07

Total Pages: 393

ISBN-13: 0691222746

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Data science methods and tools—including programming, data management, visualization, and machine learning—and their application to neuroimaging research As neuroimaging turns toward data-intensive discovery, researchers in the field must learn to access, manage, and analyze datasets at unprecedented scales. Concerns about reproducibility and increased rigor in reporting of scientific results also demand higher standards of computational practice. This book offers neuroimaging researchers an introduction to data science, presenting methods, tools, and approaches that facilitate automated, reproducible, and scalable analysis and understanding of data. Through guided, hands-on explorations of openly available neuroimaging datasets, the book explains such elements of data science as programming, data management, visualization, and machine learning, and describes their application to neuroimaging. Readers will come away with broadly relevant data science skills that they can easily translate to their own questions. • Fills the need for an authoritative resource on data science for neuroimaging researchers • Strong emphasis on programming • Provides extensive code examples written in the Python programming language • Draws on openly available neuroimaging datasets for examples • Written entirely in the Jupyter notebook format, so the code examples can be executed, modified, and re-executed as part of the learning process