This work is an attempt to fill the gap between high level image analysis and low level feature detectors for volumetric imaging data. It proposes both a representation model and an extraction technique for 3D spectral features. This approach is not limited to a multiresolution decomposition, but it goes a step further, rearranging frequency bands to group correlated information together. The whole process is based on minimal assumptions, inspired in theories about the human visual system. The method is completely data-driven; no prior information is used. The performance of the method is tested in a variety of volumetric imaging applications: 3D medical image segmentation (MRI and SPECT), and analysis of Ground Penetrating Radar (GPR) data and Tagged Magnetic Resonance (TMR) image sequences. The methods presented in this book can be of interest for researchers in the field of image processing in general and, in particular, for scientist and engineers working in analysis of volumetric data of any kind.
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This work is an attempt to fill the gap between high level image analysis and low level feature detectors for volumetric imaging data. It proposes both a representation model and an extraction technique for 3D spectral features. This approach is not limited to a multiresolution decomposition, but it goes a step further, rearranging frequency bands to group correlated information together. The whole process is based on minimal assumptions, inspired in theories about the human visual system. The method is completely data-driven; no prior information is used. The performance of the method is tested in a variety of volumetric imaging applications: 3D medical image segmentation (MRI and SPECT), and analysis of Ground Penetrating Radar (GPR) data and Tagged Magnetic Resonance (TMR) image sequences. The methods presented in this book can be of interest for researchers in the field of image processing in general and, in particular, for scientist and engineers working in analysis of volumetric data of any kind. 152 pp. Englisch. Seller Inventory # 9783838342122
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This work is an attempt to fill the gap between high level image analysis and low level feature detectors for volumetric imaging data. It proposes both a representation model and an extraction technique for 3D spectral features. This approach is not limited to a multiresolution decomposition, but it goes a step further, rearranging frequency bands to group correlated information together. The whole process is based on minimal assumptions, inspired in theories about the human visual system. The method is completely data-driven; no prior information is used. The performance of the method is tested in a variety of volumetric imaging applications: 3D medical image segmentation (MRI and SPECT), and analysis of Ground Penetrating Radar (GPR) data and Tagged Magnetic Resonance (TMR) image sequences. The methods presented in this book can be of interest for researchers in the field of image processing in general and, in particular, for scientist and engineers working in analysis of volumetric data of any kind. Seller Inventory # 9783838342122
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Dosil RaquelRaquel Dosil Lago: BSc in Physics, PhD in Computer Vision. Postdoctoral researcher at Universidade de Santiago de Compostela.This work is an attempt to fill the gap between high level image analysis and low level f. Seller Inventory # 5414709
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Taschenbuch. Condition: Neu. Data Driven Synthesis of Composite-Feature Detectors | Application to the Analysis of Volumetric Imaging | Raquel Dosil | Taschenbuch | 152 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838342122 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 101118101
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This work is an attempt to fill the gap between high level image analysis and low level feature detectors for volumetric imaging data. It proposes both a representation model and an extraction technique for 3D spectral features. This approach is not limited to a multiresolution decomposition, but it goes a step further, rearranging frequency bands to group correlated information together. The whole process is based on minimal assumptions, inspired in theories about the human visual system. The method is completely data-driven; no prior information is used. The performance of the method is tested in a variety of volumetric imaging applications: 3D medical image segmentation (MRI and SPECT), and analysis of Ground Penetrating Radar (GPR) data and Tagged Magnetic Resonance (TMR) image sequences. The methods presented in this book can be of interest for researchers in the field of image processing in general and, in particular, for scientist and engineers working in analysis of volumetric data of any kind.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 152 pp. Englisch. Seller Inventory # 9783838342122
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