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Complex analysis --- Mathematical statistics --- Physical methods for diagnosis --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- patroonherkenning --- beeldverwerking --- beeldanalyse --- factoranalyse --- complexe analyse (wiskunde) --- grafische vormgeving --- radiologie --- medische beeldvorming --- robots
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This book constitutes the refereed proceedings of the Third International Workshop on Multimodal Brain Image Analysis, MBIA 2013, held in Nagoya, Japan, on September 22, 2013 in conjunction with the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI. The 24 revised full papers presented were carefully reviewed and selected from 35 submissions. The papers are organized in topical sections on analysis, methodologies, algorithms, software systems, validation approaches, benchmark datasets, neuroscience and clinical applications.
Complex analysis --- Mathematical statistics --- Physical methods for diagnosis --- Computer science --- Computer architecture. Operating systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- computervisie --- patroonherkenning --- beeldverwerking --- beeldanalyse --- factoranalyse --- complexe analyse (wiskunde) --- bedrijfssoftware --- computers --- grafische vormgeving --- pneumologie --- radiologie --- medische beeldvorming --- KI (kunstmatige intelligentie) --- computerkunde --- robots --- optica
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"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 geneticsIntroduces a novel, large-scale analytic framework that involves multi-site, image-wide, genome-wide associations"--
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