Regional appearance modeling for model-based image segmentation: Methodological approaches to improve the accuracy of model-based image segmentation - Softcover
Synopsis
This thesis presents a novel appearance prior for model-based image segmentation. This appearance prior, denoted as Multimodal Prior Appearance Model (MPAM), is built upon an EM clustering of intensity profiles with model order selection to automatically select the number of profile classes. Unlike classical PCA-based approaches, the clustering is considered as regional because intensity profiles are classified for each mesh and not for each vertex. Comparative results on liver profiles from CT images show that MPAM outperforms PCA-based appearance models. Finally, methods for the analysis of lower limb structures from MR images are presented. A first part deals with the creation of subject-specific models for kinematic simulations of the lower limbs. In a second part, the performance of statistical models is compared in the context of lower limb bone segmentation when only a small number of datasets is available for training.
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About the Author
Since January 2011, François Chung holds a Ph.D. in medical image analysis from Mines ParisTech, France. His Ph.D. was done within the Asclepios Research Team, INRIA Sophia-Antipolis, France. In 2005, François Chung graduated industrial engineer in computer science (Ing., M.Sc.) from the Institut Supérieur Industriel de Bruxelles (ISIB), Belgium.
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Regional appearance modeling for model-based image segmentation
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This thesis presents a novel appearance prior for model-based image segmentation. This appearance prior, denoted as Multimodal Prior Appearance Model (MPAM), is built upon an EM clustering of intensity profiles with model order selection to automatically select the number of profile classes. Unlike classical PCA-based approaches, the clustering is considered as regional because intensity profiles are classified for each mesh and not for each vertex. Comparative results on liver profiles from CT images show that MPAM outperforms PCA-based appearance models. Finally, methods for the analysis of lower limb structures from MR images are presented. A first part deals with the creation of subject-specific models for kinematic simulations of the lower limbs. In a second part, the performance of statistical models is compared in the context of lower limb bone segmentation when only a small number of datasets is available for training. 196 pp. Englisch. Seller Inventory # 9783844322095
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Regional appearance modeling for model-based image segmentation | Methodological approaches to improve the accuracy of model-based image segmentation
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Taschenbuch. Condition: Neu. Regional appearance modeling for model-based image segmentation | Methodological approaches to improve the accuracy of model-based image segmentation | François Chung | Taschenbuch | 196 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783844322095 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Seller Inventory # 107061546
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Taschenbuch. Condition: Neu. Neuware -This thesis presents a novel appearance prior for model-based image segmentation. This appearance prior, denoted as Multimodal Prior Appearance Model (MPAM), is built upon an EM clustering of intensity profiles with model order selection to automatically select the number of profile classes. Unlike classical PCA-based approaches, the clustering is considered as regional because intensity profiles are classified for each mesh and not for each vertex. Comparative results on liver profiles from CT images show that MPAM outperforms PCA-based appearance models. Finally, methods for the analysis of lower limb structures from MR images are presented. A first part deals with the creation of subject-specific models for kinematic simulations of the lower limbs. In a second part, the performance of statistical models is compared in the context of lower limb bone segmentation when only a small number of datasets is available for training.Books on Demand GmbH, Überseering 33, 22297 Hamburg 196 pp. Englisch. Seller Inventory # 9783844322095
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Regional appearance modeling for model-based image segmentation : Methodological approaches to improve the accuracy of model-based image segmentation
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This thesis presents a novel appearance prior for model-based image segmentation. This appearance prior, denoted as Multimodal Prior Appearance Model (MPAM), is built upon an EM clustering of intensity profiles with model order selection to automatically select the number of profile classes. Unlike classical PCA-based approaches, the clustering is considered as regional because intensity profiles are classified for each mesh and not for each vertex. Comparative results on liver profiles from CT images show that MPAM outperforms PCA-based appearance models. Finally, methods for the analysis of lower limb structures from MR images are presented. A first part deals with the creation of subject-specific models for kinematic simulations of the lower limbs. In a second part, the performance of statistical models is compared in the context of lower limb bone segmentation when only a small number of datasets is available for training. Seller Inventory # 9783844322095
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