Multi Modality Inference Methods For Neuroimaging With Applications To Alzheimers Disease Research
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| Author | : National Academies of Sciences Engineering and Medicine |
| Publisher | : |
| Total Pages | : |
| Release | : 2022-04-26 |
| Genre | : |
| ISBN | : 9780309495035 |
As the largest generation in U.S. history - the population born in the two decades immediately following World War II - enters the age of risk for cognitive impairment, growing numbers of people will experience dementia (including Alzheimer's disease and related dementias). By one estimate, nearly 14 million people in the United States will be living with dementia by 2060. Like other hardships, the experience of living with dementia can bring unexpected moments of intimacy, growth, and compassion, but these diseases also affect people's capacity to work and carry out other activities and alter their relationships with loved ones, friends, and coworkers. Those who live with and care for individuals experiencing these diseases face challenges that include physical and emotional stress, difficult changes and losses in their relationships with life partners, loss of income, and interrupted connections to other activities and friends. From a societal perspective, these diseases place substantial demands on communities and on the institutions and government entities that support people living with dementia and their families, including the health care system, the providers of direct care, and others. Nevertheless, research in the social and behavioral sciences points to possibilities for preventing or slowing the development of dementia and for substantially reducing its social and economic impacts. At the request of the National Institute on Aging of the U.S. Department of Health and Human Services, Reducing the Impact of Dementia in America assesses the contributions of research in the social and behavioral sciences and identifies a research agenda for the coming decade. This report offers a blueprint for the next decade of behavioral and social science research to reduce the negative impact of dementia for America's diverse population. Reducing the Impact of Dementia in America calls for research that addresses the causes and solutions for disparities in both developing dementia and receiving adequate treatment and support. It calls for research that sets goals meaningful not just for scientists but for people living with dementia and those who support them as well. By 2030, an estimated 8.5 million Americans will have Alzheimer's disease and many more will have other forms of dementia. Through identifying priorities social and behavioral science research and recommending ways in which they can be pursued in a coordinated fashion, Reducing the Impact of Dementia in America will help produce research that improves the lives of all those affected by dementia.
| Author | : Judith Pratt |
| Publisher | : Springer |
| Total Pages | : 431 |
| Release | : 2019-01-05 |
| Genre | : Medical |
| ISBN | : 3319996428 |
This volume addresses one of the Holy Grails in Psychiatry, namely the evidence for and potential to adopt ‘Biomarkers’ for prevention, diagnosis, and treatment responses in mental health conditions. It meshes together state of the art research from international renowned pre-clinical and clinical scientists to illustrate how the fields of anxiety disorders, depression, psychotic disorders, and autism spectrum disorder have advanced in recent years.
| Author | : Frederik Barkhof |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 295 |
| Release | : 2011-02-11 |
| Genre | : Medical |
| ISBN | : 3642008186 |
This up-to-date, superbly illustrated book is a practical guide to the effective use of neuroimaging in the patient with cognitive decline. It sets out the key clinical and imaging features of the various causes of dementia and directs the reader from clinical presentation to neuroimaging and on to an accurate diagnosis whenever possible. After an introductory chapter on the clinical background, the available "toolbox" of structural and functional neuroimaging techniques is reviewed in detail, including CT, MRI and advanced MR techniques, SPECT and PET, and image analysis methods. The imaging findings in normal ageing are then discussed, followed by a series of chapters that carefully present and analyze the key findings in patients with dementias. Throughout, a practical approach is adopted, geared specifically to the needs of clinicians (neurologists, radiologists, psychiatrists, geriatricians) working in the field of dementia, for whom this book will prove an invaluable resource.
| Author | : Xiaoying Tang |
| Publisher | : Frontiers Media SA |
| Total Pages | : 118 |
| Release | : 2019-08-22 |
| Genre | : |
| ISBN | : 2889459845 |
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.
| Author | : W.Wolfgang Fleischhacker |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 164 |
| Release | : 2002-11-07 |
| Genre | : Medical |
| ISBN | : 9783211838662 |
Atherosclerosis, the underlying cause of heart attacks, strokes and peripheral vascular disease, is one of the major killers in the world. By 2020 WHO statistics indicate that it will be the most common cause of morbidity and mortality in both the industrialised world and the underdeveloped world. The disease develops slowly over many years in the innermost layer of large and medium-sized arteries (Fig. 1) (Scott, 1995; Ross, 1999; Naumova and Scott, 2000; Glass and Witztum, 2001; Libby, 2001). It does not usually become manifest before the fourth of fifth decade, but then often strikes with devas tating suddenness. Fifty per cent of individuals still die (25 per cent immedi ately) from their first heart attack; and morbidity from coronary heart disease and stroke is very significant. The disease has a profound impact on health care services and on industrial economies. The lesions of atherosclerosis Autopsy studies show that in humans atherosclerosis begins in the first and second decade of life. A similar disease can be produced in experimental animals, where diet and genetics can be manipulated to produce identical lesions. The earliest lesions are fatty streaks. These consist of an accumulation of lipid-engorged macrophages (foam cells) and T and B lymphocytes in the arterial intima. With time, the fatty streaks progress to intermediate lesions, composed of foam cells and smooth muscle cells.
| Author | : Jerry L. Prince |
| Publisher | : Springer |
| Total Pages | : 744 |
| Release | : 2009-07-30 |
| Genre | : Computers |
| ISBN | : 364202498X |
This book constitutes the refeered proceedings of the 21st International Conference on Information Processing in Medical Imaging, IPMI 2009, held in Williamsburg, VA, USA, in July 2009 The 26 revised full papers and 33 revised poster papers presented were carefully reviewed and selected from 150 submissions. The papers are organized in topical sections on diffusion imaging, PET imaging, image registration, functional networks, space curves, tractography, microscopy, exploratory analyses, features and detection, image guided surgery, shape analysis, motion, and segmentation and validation.
| Author | : Islem Rekik |
| Publisher | : |
| Total Pages | : 174 |
| Release | : 2018 |
| Genre | : Artificial intelligence |
| ISBN | : 9783030003210 |
This book constitutes the refereed proceedings of the First International Workshop on PRedictive Intelligence in MEdicine, PRIME 2018, held in conjunction with MICCAI 2018, in Granada, Spain, in September 2018. The 20 full papers presented were carefully reviewed and selected from 23 submissions. The main aim of the workshop is to propel the advent of predictive models in a broad sense, with application to medical data. Particularly, the workshop will admit papers describing new cutting-edge predictive models and methods that solve challenging problems in the medical field.
| Author | : Derek K Jones |
| Publisher | : Oxford University Press |
| Total Pages | : 784 |
| Release | : 2010-11-11 |
| Genre | : Science |
| ISBN | : 0199708703 |
Professor Derek Jones, a world authority on diffusion MRI, has assembled most of the world's leading scientists and clinicians developing and applying diffusion MRI to produce an authorship list that reads like a "Who's Who" of the field and an essential resource for those working with diffusion MRI. Destined to be a modern classic, this definitive and richly illustrated work covers all aspects of diffusion MRI from basic theory to clinical application. Oxford Clinical Neuroscience is a comprehensive, cross-searchable collection of resources offering quick and easy access to eleven of Oxford University Press's prestigious neuroscience texts. Joining Oxford Medicine Online these resources offer students, specialists and clinical researchers the best quality content in an easy-to-access format.
| Author | : Hao Zhang |
| Publisher | : Frontiers Media SA |
| Total Pages | : 151 |
| Release | : 2024-10-14 |
| Genre | : Science |
| ISBN | : 2832555500 |
Brain imaging has been successfully used to generate image-based biomarkers for various neurological and psychiatric disorders, such as Alzheimer’s and related dementias, Parkinson’s disease, stroke, traumatic brain injury, brain tumors, depression, schizophrenia, etc. However, accurate brain image-based diagnosis at the individual level remains elusive, and this applies to the diagnosis of neuropathological diseases as well as clinical syndromes. In recent years, deep learning techniques, due to their ability to learn complex patterns from large amounts of data, have had remarkable success in various fields, such as computer vision and natural language processing. Applying deep learning methods to brain imaging-assisted diagnosis, while promising, is facing challenges such as insufficiently labeled data, difficulty in interpreting diagnosis results, variations in data acquisition in multi-site projects, integration of multimodal data, clinical heterogeneity, etc. The goal of this research topic is to gather cutting-edge research that showcases the application of deep learning methods in brain imaging for the diagnosis of neurological and psychiatric disorders. We encourage submissions that demonstrate novel approaches to overcome various abovementioned difficulties and achieve more accurate, reliable, generalizable, and interpretable diagnosis of neurological and psychiatric disorders in this field.
| Author | : Erik R. Ranschaert |
| Publisher | : Springer |
| Total Pages | : 369 |
| Release | : 2019-01-29 |
| Genre | : Medical |
| ISBN | : 3319948784 |
This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.
