Regional appearance modeling for model-based image segmentation: Methodological approaches to improve the accuracy of model-based image segmentation - Softcover

Chung, François

 
9783844322095: Regional appearance modeling for model-based image segmentation: Methodological approaches to improve the accuracy of model-based image segmentation
Softcover
ISBN 10: 3844322094 ISBN 13: 9783844322095
Verlag: LAP LAMBERT Academic Publishing, 2011

Inhaltsangabe

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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Reseña del editor

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.

Biografía del autor

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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Verlag
LAP LAMBERT Academic Publishing
Erscheinungsdatum
2011
Sprache
Englisch
ISBN 10 
3844322094
ISBN 13 
9783844322095
Einband
Tapa blanda
Anzahl der Seiten
196
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Verantwortliche Person
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