Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Imaging Genetics PDF full book. Access full book title Imaging Genetics by Adrian Dalca. Download full books in PDF and EPUB format.
Author: Adrian Dalca Publisher: Academic Press ISBN: 0128139692 Category : Technology & Engineering Languages : en Pages : 202
Book Description
Imaging Genetics presents the latest research in imaging genetics methodology for discovering new associations between imaging and genetic variables, providing an overview of the state-of the-art in the field. Edited and written by leading researchers, this book is a beneficial reference for students and researchers, both new and experienced, in this growing area. The field of imaging genetics studies the relationships between DNA variation and measurements derived from anatomical or functional imaging data, often in the context of a disorder. While traditional genetic analyses rely on classical phenotypes like clinical symptoms, imaging genetics can offer richer insights into underlying, complex biological mechanisms. Contains an introduction describing how the field has evolved to the present, together with perspectives on its future direction and challenges Describes novel application domains and analytic methods that represent the state-of-the-art in the burgeoning field of imaging genetics Introduces a novel, large-scale analytic framework that involves multi-site, image-wide, genome-wide associations
Author: Adrian Dalca Publisher: Academic Press ISBN: 0128139692 Category : Technology & Engineering Languages : en Pages : 202
Book Description
Imaging Genetics presents the latest research in imaging genetics methodology for discovering new associations between imaging and genetic variables, providing an overview of the state-of the-art in the field. Edited and written by leading researchers, this book is a beneficial reference for students and researchers, both new and experienced, in this growing area. The field of imaging genetics studies the relationships between DNA variation and measurements derived from anatomical or functional imaging data, often in the context of a disorder. While traditional genetic analyses rely on classical phenotypes like clinical symptoms, imaging genetics can offer richer insights into underlying, complex biological mechanisms. Contains an introduction describing how the field has evolved to the present, together with perspectives on its future direction and challenges Describes novel application domains and analytic methods that represent the state-of-the-art in the burgeoning field of imaging genetics Introduces a novel, large-scale analytic framework that involves multi-site, image-wide, genome-wide associations
Author: Kristin L. Bigos Publisher: Oxford University Press ISBN: 0190209771 Category : Medical Languages : en Pages : 433
Book Description
The field of neuroimaging genetics has grown exponentially over the past decade. To date there are more than 10,000 published papers involving MRI, PET, MEG and genetics. Neuroimaging Genetics: Principles and Practices is the comprehensive volume edited by Drs. Bigos, Hariri, and Weinberger and co-authored by the preeminent scholars in the field. This text reviews the basic principles of neuroimaging techniques and their application to neuroimaging genetics. The work presented in this volume elaborates on the explosive interest from diverse research areas in psychiatry and neurology in the use of imaging genetics as a unique tool to establish and identify mechanisms of risk, establish biological significance, and extend statistical evidence of genetic associations. Examples throughout highlight the application of imaging genetics to understand neurochemical systems and pathways, explore relationships between genetics and the structural and functional connectivity in human brain, and provide insight into mechanisms of risk for psychiatric and neurologic illness.
Author: Luis Celso Hygino de Cruz Publisher: Elsevier Health Sciences ISBN: 0323354637 Category : Medical Languages : en Pages : 209
Book Description
Genetic Patterns in Neuroimaging is explored in this important Neuroimaging Clinics issue. Articles include: Brain imaging and genetic risk of congenital malformations; Understanding genetics in neuroimaging; Influence of genetics in neuropathology; Building a bridge between genomics and neuroradiology; Systems genetics approaches to neuroimaging phenotypes; Imaging genetic predictions at an individual level; Brain imaging and genetic risk in the pediatric population; Imaging phenotypes in cognitive diseases; Molecular imaging in genetics; Imaging phenotypes in psychiatric disease; Genomics of brain tumor imaging; Neuroimaging and genetic influence in post-treatment brain neoplasms; Imaging phenotypes in multiple sclerosis; Genetic markers and influences in cerebrovascular malformations, and more.
Author: Marek Kubicki Publisher: Springer Nature ISBN: 3030352064 Category : Medical Languages : en Pages : 432
Book Description
This comprehensive book explains the importance of imaging techniques in exploring and understanding the role of brain abnormalities in schizophrenia. The findings obtained using individual imaging modalities and their biological interpretation are reviewed in detail, and updates are provided on methodology, testable hypotheses, limitations, and new directions for research. The coverage also includes important recent applications of neuroimaging to schizophrenia, for example in relation to non-pharmacological interventions, brain development, genetics, and prediction of treatment response and outcome. Written by world renowned experts in the field, the book will be invaluable to all who wish to learn about the newest and most important developments in neuroimaging research in schizophrenia, how these developments relate to the last 30 years of research, and how they can be leveraged to bring us closer to a cure for this devastating disorder. Neuroimaging in Schizophrenia will assist clinicians in navigating what is an extremely complex field and will be a source of insight and stimulation for researchers.
Author: Guorong Wu Publisher: Academic Press ISBN: 0128041145 Category : Computers Languages : en Pages : 514
Book Description
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
Author: G. Bradley Schaefer Publisher: McGraw Hill Professional ISBN: 0071819282 Category : Medical Languages : en Pages : 385
Book Description
A complete introductory text on how to integrate basic genetic principles into the practice of clinical medicine Medical Genetics is the first text to focus on the everyday application of genetic assessment and its diagnostic, therapeutic, and preventive implications in clinical practice. It is intended to be a text that you can use throughout medical school and refer back to when questions arise during residency and, eventually, practice. Medical Genetics is written as a narrative where each chapter builds upon the foundation laid by previous ones. Chapters can also be used as stand-alone learning aids for specific topics. Taken as a whole, this timely book delivers a complete overview of genetics in medicine. You will find in-depth, expert coverage of such key topics as: The structure and function of genes Cytogenetics Mendelian inheritance Mutations Genetic testing and screening Genetic therapies Disorders of organelles Key genetic diseases, disorders, and syndromes Each chapter of Medical Genetics is logically organized into three sections: Background and Systems – Includes the basic genetic principles needed to understand the medical application Medical Genetics – Contains all the pertinent information necessary to build a strong knowledge base for being successful on every step of the USMLE Case Study Application – Incorporates case study examples to illustrate how basic principles apply to real-world patent care Today, with every component of health care delivery requiring a working knowledge of core genetic principles, Medical Genetics is a true must-read for every clinician.
Author: M. Jorge Cardoso Publisher: Springer ISBN: 331967675X Category : Computers Languages : en Pages : 262
Book Description
This book constitutes the refereed joint proceedings of the First International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2017, the 6th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2017, and the Third International Workshop on Imaging Genetics, MICGen 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Québec City, QC, Canada, in September 2017. The 7 full papers presented at GRAIL 2017, the 10 full papers presented at MFCA 2017, and the 5 full papers presented at MICGen 2017 were carefully reviewed and selected. The GRAIL papers cover a wide range of graph based medical image analysis methods and applications, including probabilistic graphical models, neuroimaging using graph representations, machine learning for diagnosis prediction, and shape modeling. The MFCA papers deal with theoretical developments in non-linear image and surface registration in the context of computational anatomy. The MICGen papers cover topics in the field of medical genetics, computational biology and medical imaging.
Author: Liu Shu Publisher: ISBN: 9789464891522 Category : Languages : en Pages : 0
Book Description
"While the investigation into complex human traits has extended for over a century, the mechanisms underlying many of them remain poorly understood. Imaging genetics is an interdisciplinary field that integrates genetic and neuroimaging techniques to explore the influence of genetic variations on brain structure and function, subsequently impacting complex traits. This thesis aims to identify the neural mechanisms underlying complex traits within the framework of imaging genetics. First, a systematic exploration of genetic relationships between the brain and various traits revealed distinct associations between brain structure/function and genetic predispositions to mental health and cognition. Second, we established links between gene expression and the neural correlates of major depressive disorder and risky behaviors, suggesting the intermediary processes bridging genes and their associated brain patterns. Addressing concerns about the replicability of neuroimaging analyses, the third objective of the thesis was to assess the replicability of brain-phenotype associations across various traits within different domains, emphasizing that large-scale neuroimaging data are required for replicable brain–phenotype associations. These findings have yielded valuable insights into the neural mechanisms underpinning complex traits, offering robust evidence for the pivotal roles of the brain in the pathways from genotype to phenotype."--
Author: Federico Bermudez-Rattoni Publisher: CRC Press ISBN: 1420008412 Category : Psychology Languages : en Pages : 368
Book Description
A comprehensive, multidisciplinary review, Neural Plasticity and Memory: From Genes to Brain Imaging provides an in-depth, up-to-date analysis of the study of the neurobiology of memory. Leading specialists share their scientific experience in the field, covering a wide range of topics where molecular, genetic, behavioral, and brain imaging techniq
Author: Tao Yang Publisher: ISBN: Category : Machine learning Languages : en Pages : 124
Book Description
Imaging genetics is an emerging and promising technique that investigates how genetic variations affect brain development, structure, and function. By exploiting disorder-related neuroimaging phenotypes, this class of studies provides a novel direction to reveal and understand the complex genetic mechanisms. Oftentimes, imaging genetics studies are challenging due to the relatively small number of subjects but extremely high-dimensionality of both imaging data and genomic data. In this dissertation, I carry on my research on imaging genetics with particular focuses on two tasks---building predictive models between neuroimaging data and genomic data, and identifying disorder-related genetic risk factors through image-based biomarkers. To this end, I consider a suite of structured sparse methods---that can produce interpretable models and are robust to overfitting---for imaging genetics. With carefully-designed sparse-inducing regularizers, different biological priors are incorporated into learning models. More specifically, in the Allen brain image--gene expression study, I adopt an advanced sparse coding approach for image feature extraction and employ a multi-task learning approach for multi-class annotation. Moreover, I propose a label structured-based two-stage learning framework, which utilizes the hierarchical structure among labels, for multi-label annotation. In the Alzheimer's disease neuroimaging initiative (ADNI) imaging genetics study, I employ Lasso together with EDPP (enhanced dual polytope projections) screening rules to fast identify Alzheimer's disease risk SNPs. I also adopt the tree-structured group Lasso with MLFre (multi-layer feature reduction) screening rules to incorporate linkage disequilibrium information into modeling. Moreover, I propose a novel absolute fused Lasso model for ADNI imaging genetics. This method utilizes SNP spatial structure and is robust to the choice of reference alleles of genotype coding. In addition, I propose a two-level structured sparse model that incorporates gene-level networks through a graph penalty into SNP-level model construction. Lastly, I explore a convolutional neural network approach for accurate predicting Alzheimer's disease related imaging phenotypes. Experimental results on real-world imaging genetics applications demonstrate the efficiency and effectiveness of the proposed structured sparse methods.
Author: Adrian Dalca
Author: Adrian Dalca
Author: Kristin L. Bigos
Author: Luis Celso Hygino de Cruz
Author: Marek Kubicki
Author: Guorong Wu
Author: G. Bradley Schaefer
Author: M. Jorge Cardoso
Author: Liu Shu
Author: Federico Bermudez-Rattoni
Author: Tao Yang