Multimodal Neuroimaging Computing for the Characterization of Neurodegenerative Disorders: Springer Theses
Autor Sidong Liuen Limba Engleză Hardback – 18 ian 2017
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.
Toate formatele și edițiile | Preț | Express |
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Paperback (1) | 614.85 lei 6-8 săpt. | |
Springer Nature Singapore – 30 apr 2018 | 614.85 lei 6-8 săpt. | |
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Springer Nature Singapore – 18 ian 2017 | 620.74 lei 6-8 săpt. |
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Specificații
ISBN-13: 9789811035326
ISBN-10: 9811035326
Pagini: 136
Ilustrații: XXV, 136 p. 35 illus., 14 illus. in color.
Dimensiuni: 155 x 235 x 11 mm
Greutate: 0.41 kg
Ediția:1st ed. 2017
Editura: Springer Nature Singapore
Colecția Springer
Seria Springer Theses
Locul publicării:Singapore, Singapore
ISBN-10: 9811035326
Pagini: 136
Ilustrații: XXV, 136 p. 35 illus., 14 illus. in color.
Dimensiuni: 155 x 235 x 11 mm
Greutate: 0.41 kg
Ediția:1st ed. 2017
Editura: Springer Nature Singapore
Colecția Springer
Seria Springer Theses
Locul publicării:Singapore, Singapore
Cuprins
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.
Notă biografică
Sidong Liu received his Bachelor Degree in Bioinformatics from Harbin Institute of Technology (HIT) in 2007. He then obtained a Master of Applied Science with a major in Bioinformatics in 2009, and a Master of IT with a major in Computer Science at the University of Sydney. He conducted his PhD study with a focus on medical image computing in the Biomedical and Multimedia Information Technology(BMIT) Research Group at the School of Information Technologies, the University of Sydney.
During his PhD study, supported by an Australian Postgraduate Award (APA),
Australia Alzheimer’s Disease Research Foundation (AADRF) Top-up Scholarship
and Australia Sydney University Graduates Union North America (SUGUNA) Travel
Grant, he spent one year at the Surgical Planning Laboratory (SPL), Harvard Medical School, as a visiting scholar in 2014. He was awarded a PhD Degree in Dec 2015, and his PhD thesis has received the Springer Thesis Award. He is currently a postdoctoral researchfellow with School of Information Technologies, the University of Sydney. His research interests include neuroimage computing, computational neuroscience, biomedical and health informatics, machine learning and big data analytics and its applications in biomedicine.
Textul de pe ultima copertă
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.
Caracteristici
Broadens readers’ understanding of neurodegenerative disorders and other neuropsychiatric disorders Demystifies the often confusing picture of multimodal neuroimaging processing with step-by-step examples Shares essential insights into medical image informatics, from basic image processing to advanced translational model development Includes supplementary material: sn.pub/extras