Connectomics: Applications to Neuroimaging

Connectomics: Applications to Neuroimaging is unique in presenting the frontier of neuro-applications using brain connectomics techniques. The book describes state-of-the-art research that applies brain connectivity analysis techniques to a broad range of neurological and psychiatric disorders (Alzheimer's, epilepsy, stroke, autism, Parkinson's, drug or alcohol addiction, depression, bipolar, and schizophrenia), brain fingerprint applications, speech-language assessments, and cognitive assessment.

With this book the reader will learn:

Basic mathematical principles underlying connectomics How connectomics is applied to a wide range of neuro-applications What is the future direction of connectomics techniques.

This book is an ideal reference for researchers and graduate students in computer science, data science, computational neuroscience, computational physics, or mathematics who need to understand how computational models derived from brain connectivity data are being used in clinical applications, as well as neuroscientists and medical researchers wanting an overview of the technical methods.

Features:

Combines connectomics methods with relevant and interesting neuro-applications Covers most of the hot topics in neuroscience and clinical areas Appeals to researchers in a wide range of disciplines: computer science, engineering, data science, mathematics, computational physics, computational neuroscience, as well as neuroscience, and medical researchers interested in the technical methods of connectomics

Edited by:   Brent C. Munsell (College of Charleston South Carolina USA), Guorong Wu (Assistant Professor of Radiology and Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, USA), Leonardo Bonilha (The Medical University of South Carolina, Charleston, SC, USA), Paul Laurienti (Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC, USA)
Imprint:   Academic Press Inc
Country of Publication:   United States
Dimensions:   Height: 235mm,  Width: 191mm, 
Weight:   630g
ISBN:   9780128138380
ISBN 10:   0128138386
Pages:   233
Publication Date:   September 2018
Audience:   College/higher education ,  Professional and scholarly ,  Further / Higher Education ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active

Brent C. Munsell is an Assistant Professor in the Department of Computer Science at the College of Charleston, US. He received a Ph.D. degree in Computer Science and Engineering from the University of South Carolina, a Masters degree in Electrical Engineering from Clemson University, and a B.S. degree in Electrical Engineering from Michigan State University. Dr. Munsell's research aims to develop computational tools that draw inferences from biomedical imaging data, particular in the context of brain connectivity and network analysis. He is interested in medical image analysis, machine learning, and computer vision. Dr. Munsell has published papers in several top journals such as Nature, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Medical Imaging, International Journal of Computer Vision and NeuroImage, and is actively working on structural and functional connectivity research projects that will allow clinicians to diagnose children who may have an Autism spectrum disorder before the age of two years old. Guorong Wu is an Assistant Professor of Radiology and Biomedical Research Imaging Center (BRIC) in the University of North Carolina at Chapel Hill. Dr. Wu received his PhD degree from the Department of Computer Science in Shanghai Jiao Tong University in 2007. After graduation, he worked for Pixelworks and joined University of North Carolina at Chapel Hill in 2009. Dr. Wu's research aims to develop computational tools for biomedical imaging analysis and computer assisted diagnosis. He is interested in medical image processing, machine learning and pattern recognition. He has published more than 100 papers in the international journals and conferences. Dr. Wu is actively in the development of medical image processing software to facilitate the scientific research on neuroscience and radiology therapy. Dr Leonardo Bonilha is a neurologist and clinical researcher, working within neurophysiology, epilepsy, language problems and stroke. His research focuses on understanding structural and functional network adaptations to brain injury, particularly regarding language impairments (aphasia) after stroke and its recovery. He also studies neuronal networks associated with epilepsy and its response to treatment. His main research tools focus around Structural and functional MRI, neurophysiology (scalp and intracranial EEG) as well as behavioral language treatments for language. Paul Laurienti completed his MD and PhD training at the University of Texas Medical Branch at Galveston in 1999. He completed a research fellowship at Wake Forest School of Medicine and became an assistant professor in the Department of Radiology in 2002. He has since achieved the level of tenured full professor and has published over 100 peer-reviewed manuscripts. He is the Director of the Laboratory for Complex Brain Networks and leads an interdisciplinary group of scientists. They use functional and structural brain imaging combined with network science to study the brain as an integrated system. His current research focuses on methodological development and the application of network methods to neuroscientific questions.