Multimodal Neuroimaging Computing for the Characterization of Neurodegenerative Disorders

This thesis covers various facets of brain image computing methods and illustrates the scientific understanding of neurodegenerative disorders based on four general aspects of multimodal neuroimaging computing: neuroimaging data pre-processing, brain feature modeling, pathological pattern analysis, and translational model development. It demonstrates how multimodal neuroimaging computing techniques can be integrated and applied to neurodegenerative disease research and management, highlighting relevant examples and case studies. Readers will also discover a number of interesting extension topics in longitudinal neuroimaging studies, subject-centered analysis, and the brain connectome. As such, the book will benefit all health informatics postgraduates, neuroscience researchers, neurology and psychiatry practitioners, and policymakers who are interested in medical image computing and computer-assisted interventions.

Inhalt

Introduction.- Background.- Datasets and Pre-processing.- Neurodegenerative Feature Modeling and Learning.- Neurodegenerative Pattern Analysis.- Alzheimer's Disease Staging and Prediction.- Neuroimaging Content-Based Retrieval.- Conclusions and Future Directions.