Tomographic Reconstruction of Label Images Using Gibbs Priors: Parameter Estimation, Methods, Algorithms - Softcover
Synopsis
In many applications of tomography, such as electron microscopy, industrial non-destructive testing, cardiac imaging, etc, the aim is to find the components constituting the object. Traditional approaches would first reconstruct the density distribution from the projection data and then segment (label) this distribution. This book introduces a new paradigm of directly estimating the label image from the projections, by postulating a low level prior knowledge regarding the underlying distribution of label images. Because of the typically small number of labels, this problem offers significant challenges and opportunity: much fewer data is required as a result. This work provides strategies, algorithms, as well as methods for choosing suitable Gibbs prior. Anyone who may be considering reconstructing label images from limited data should find this book a useful guide.
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About the Author
Hstau Y Liao is a research scientist at Columbia University Medical Center. His research interest comprises tomography, image processing, optimization, and high-dimensional data modeling. Hstau was invited to consult for Toshiba. He won in various mathematical contests, including the IMO. Hstau is also interested in macroeconomics.
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Tomographic Reconstruction of Label Images Using Gibbs Priors
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LAP LAMBERT Academic Publishing Mai 2010, 2010
ISBN 10: 3838313070
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In many applications of tomography, such as electron microscopy, industrial non-destructive testing, cardiac imaging, etc, the aim is to find the components constituting the object. Traditional approaches would first reconstruct the density distribution from the projection data and then segment (label) this distribution. This book introduces a new paradigm of directly estimating the label image from the projections, by postulating a low level prior knowledge regarding the underlying distribution of label images. Because of the typically small number of labels, this problem offers significant challenges and opportunity: much fewer data is required as a result. This work provides strategies, algorithms, as well as methods for choosing suitable Gibbs prior. Anyone who may be considering reconstructing label images from limited data should find this book a useful guide. 180 pp. Englisch. Seller Inventory # 9783838313078
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Tomographic Reconstruction of Label Images Using Gibbs Priors
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Liao Hstau YHstau Y Liao is a research scientist at Columbia UniversityMedical Center. His research interest comprises tomography, imageprocessing, optimization, and high-dimensional data modeling.Hstau was invited to consult for Tos. Seller Inventory # 5412002
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Tomographic Reconstruction of Label Images Using Gibbs Priors | Parameter Estimation, Methods, Algorithms
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Taschenbuch. Condition: Neu. Tomographic Reconstruction of Label Images Using Gibbs Priors | Parameter Estimation, Methods, Algorithms | Hstau Y Liao | Taschenbuch | 180 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838313078 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Seller Inventory # 101462515
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Tomographic Reconstruction of Label Images Using Gibbs Priors
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In many applications of tomography, such as electron microscopy, industrial non-destructive testing, cardiac imaging, etc, the aim is to find the components constituting the object. Traditional approaches would first reconstruct the density distribution from the projection data and then segment (label) this distribution. This book introduces a new paradigm of directly estimating the label image from the projections, by postulating a low level prior knowledge regarding the underlying distribution of label images. Because of the typically small number of labels, this problem offers significant challenges and opportunity: much fewer data is required as a result. This work provides strategies, algorithms, as well as methods for choosing suitable Gibbs prior. Anyone who may be considering reconstructing label images from limited data should find this book a useful guide.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 180 pp. Englisch. Seller Inventory # 9783838313078
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Tomographic Reconstruction of Label Images Using Gibbs Priors : Parameter Estimation, Methods, Algorithms
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ISBN 13: 9783838313078
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In many applications of tomography, such as electron microscopy, industrial non-destructive testing, cardiac imaging, etc, the aim is to find the components constituting the object. Traditional approaches would first reconstruct the density distribution from the projection data and then segment (label) this distribution. This book introduces a new paradigm of directly estimating the label image from the projections, by postulating a low level prior knowledge regarding the underlying distribution of label images. Because of the typically small number of labels, this problem offers significant challenges and opportunity: much fewer data is required as a result. This work provides strategies, algorithms, as well as methods for choosing suitable Gibbs prior. Anyone who may be considering reconstructing label images from limited data should find this book a useful guide. Seller Inventory # 9783838313078
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Tomographic Reconstruction of Label Images Using Gibbs Priors: Parameter Estimation, Methods, Algorithms
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