The sequel to the popular lecture book entitled Biomedical Image Analysis: Tracking, this book on Biomedical Image Analysis: Segmentation tackles the challenging task of segmenting biological and medical images. The problem of partitioning multidimensional biomedical data into meaningful regions is perhaps the main roadblock in the automation of biomedical image analysis. Whether the modality of choice is MRI, PET, ultrasound, SPECT, CT, or one of a myriad of microscopy platforms, image segmentation is a vital step in analyzing the constituent biological or medical targets. This book provides a state-of-the-art, comprehensive look at biomedical image segmentation that is accessible to well-equipped undergraduates, graduate students, and research professionals in the biology, biomedical, medical, and engineering fields. Active model methods that have emerged in the last few years are a focus of the book, including parametric active contour and active surface models, active shape models,and geometric active contours that adapt to the image topology. Additionally, Biomedical Image Analysis: Segmentation details attractive new methods that use graph theory in segmentation of biomedical imagery. Finally, the use of exciting new scale space tools in biomedical image analysis is reported. Table of Contents: Introduction / Parametric Active Contours / Active Contours in a Bayesian Framework / Geometric Active Contours / Segmentation with Graph Algorithms / Scale-Space Image Filtering for Segmentation
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Scott T. Acton received the M.S. degree in electrical and computer engineering and the Ph.D. degree in electrical and computer engineering from the University of Texas at Austin in 1990 and 1993, respectively, where he was a Microelectronics and Computer Development Fellow. He received the B.S. degree in electrical engineering from Virginia Tech, Blacksburg in 1988 as a Virginia Scholar and Marshall Hahn Fellow. He was the class of 1984 valedictorian at Oakton High School in Vienna, VA. At Oakton, he was a member of the football and basketball teams, although the coach rarely let him in an actual game. He has worked in industry for AT&T, Oakton, VA, the MITRE Corporation, McLean, VA, and Motorola, Inc., Phoenix, AZ and in academia for Oklahoma State University, Stillwater. Currently, he holds the Walter N. Munster Chair for Intelligence Enhancement at the University of Virginia (U.Va.), where he is a member of the Charles L. Brown Department of Electrical and Computer Engineering and the Department of Biomedical Engineering. At U.Va., he was named the Outstanding New Teacher in 2002 and was elected a Faculty Fellow in 2003. For his research in video tracking, he was given an ARO Young Investigator Award. He received the Halliburton Outstanding Young Faculty Award in 1998. In 1997, he was named the Eta Kappa Nu Outstanding Young Electrical Engineer (a national award that has been given annually since 1936). He is the recipient of a Whitaker Foundation Biomedical Engineering Research Grant for work in cell detection and tracking. He currently is working on NIH-funded research for leukocyte tracking, segmentation of the myocardium from ultrasound, and segmentation of the myocardium from MRI. Dr. Acton is an active participant in the IEEE, served as Associate Editor for the IEEE Transactions on Image Processing and as Associate Editor for the IEEE Signal Processing Letters. He is the 2004 Technical Program Chair and the 2006 General Chair for the Asilomar Conference onSignals, Systems and Computers. His research interests include anisotropic diffusion, the history of Billy the Kid, active contours, biomedical segmentation problems, biomedical tracking problems, and war. Acton was a 2005 finalist in the Florida First Coast Novel Contest. He lives in beautiful Charlottesville, Virginia, with his wife and two boys.
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The sequel to the popular lecture book entitled Biomedical Image Analysis: Tracking, this book on Biomedical Image Analysis: Segmentation tackles the challenging task of segmenting biological and medical images. The problem of partitioning multidimensional . Codice articolo 608129361
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The sequel to the popular lecture book entitled Biomedical Image Analysis: Tracking, this book on Biomedical Image Analysis: Segmentation tackles the challenging task of segmenting biological and medical images. The problem of partitioning multidimensional biomedical data into meaningful regions is perhaps the main roadblock in the automation of biomedical image analysis. Whether the modality of choice is MRI, PET, ultrasound, SPECT, CT, or one of a myriad of microscopy platforms, image segmentation is a vital step in analyzing the constituent biological or medical targets. This book provides a state-of-the-art, comprehensive look at biomedical image segmentation that is accessible to well-equipped undergraduates, graduate students, and research professionals in the biology, biomedical, medical, and engineering fields. Active model methods that have emerged in the last few years are a focus of the book, including parametric active contour and active surface models, active shape models, and geometric active contours that adapt to the image topology. Additionally, Biomedical Image Analysis: Segmentation details attractive new methods that use graph theory in segmentation of biomedical imagery. Finally, the use of exciting new scale space tools in biomedical image analysis is reported. Table of Contents: Introduction / Parametric Active Contours / Active Contours in a Bayesian Framework / Geometric Active Contours / Segmentation with Graph Algorithms / Scale-Space Image Filtering for Segmentation 116 pp. Englisch. Codice articolo 9783031011177
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The sequel to the popular lecture book entitled Biomedical Image Analysis: Tracking, this book on Biomedical Image Analysis: Segmentation tackles the challenging task of segmenting biological and medical images. The problem of partitioning multidimensional biomedical data into meaningful regions is perhaps the main roadblock in the automation of biomedical image analysis. Whether the modality of choice is MRI, PET, ultrasound, SPECT, CT, or one of a myriad of microscopy platforms, image segmentation is a vital step in analyzing the constituent biological or medical targets. This book provides a state-of-the-art, comprehensive look at biomedical image segmentation that is accessible to well-equipped undergraduates, graduate students, and research professionals in the biology, biomedical, medical, and engineering fields. Active model methods that have emerged in the last few years are a focus of the book, including parametric active contour and active surface models, active shape models,and geometric active contours that adapt to the image topology. Additionally, Biomedical Image Analysis: Segmentation details attractive new methods that use graph theory in segmentation of biomedical imagery. Finally, the use of exciting new scale space tools in biomedical image analysis is reported. Table of Contents: Introduction / Parametric Active Contours / Active Contours in a Bayesian Framework / Geometric Active Contours / Segmentation with Graph Algorithms / Scale-Space Image Filtering for Segmentation. Codice articolo 9783031011177
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Taschenbuch. Condizione: Neu. Neuware -The sequel to the popular lecture book entitled Biomedical Image Analysis: Tracking, this book on Biomedical Image Analysis: Segmentation tackles the challenging task of segmenting biological and medical images. The problem of partitioning multidimensional biomedical data into meaningful regions is perhaps the main roadblock in the automation of biomedical image analysis. Whether the modality of choice is MRI, PET, ultrasound, SPECT, CT, or one of a myriad of microscopy platforms, image segmentation is a vital step in analyzing the constituent biological or medical targets. This book provides a state-of-the-art, comprehensive look at biomedical image segmentation that is accessible to well-equipped undergraduates, graduate students, and research professionals in the biology, biomedical, medical, and engineering fields. Active model methods that have emerged in the last few years are a focus of the book, including parametric active contour and active surface models, active shape models,and geometric active contours that adapt to the image topology. Additionally, Biomedical Image Analysis: Segmentation details attractive new methods that use graph theory in segmentation of biomedical imagery. Finally, the use of exciting new scale space tools in biomedical image analysis is reported. Table of Contents: Introduction / Parametric Active Contours / Active Contours in a Bayesian Framework / Geometric Active Contours / Segmentation with Graph Algorithms / Scale-Space Image Filtering for SegmentationSpringer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 116 pp. Englisch. Codice articolo 9783031011177
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