In medical image analysis, major areas such as radiotherapy, surgery planning, and quantitative diagnostics benefit from shape modeling to facilitate solutions to analysis, segmentation and reconstruction problems.
Heike Hufnagel proposes a mathematically sound statistical shape model using correspondence probabilities instead of 1-to-1 correspondences. The explicit probabilistic model is employed as shape prior in an implicit level set segmentation. Due to the particular attributes of the new model, the challenging integration of explicit and implicit representations can be done in an elegant mathematical formulation, thus combining the advantages of both explicit model and implicit segmentation. Evaluations are performed to depict the characteristics and strengths of the new model and segmentation method.
The dissertation has received the Fokusfinder award 2011 by the Innovationsstiftung Schleswig-Holstein (ISH), the Basler AG and Philips Medical Systems.
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Heike Hufnagel works as a research scientist at the Institute of Medical Informatics, University of Luebeck, Germany. She holds a PhD in natural sciences.
In medical image analysis, major areas such as radiotherapy, surgery planning, and quantitative diagnostics benefit from shape modeling to facilitate solutions to analysis, segmentation and reconstruction problems.
Heike Hufnagel proposes a mathematically sound statistical shape model using correspondence probabilities instead of 1-to-1 correspondences. The explicit probabilistic model is employed as shape prior in an implicit level set segmentation. Due to the particular attributes of the new model, the challenging integration of explicit and implicit representations can be done in an elegant mathematical formulation, thus combining the advantages of both explicit model and implicit segmentation. Evaluations are performed to depict the characteristics and strengths of the new model and segmentation method.
The dissertation has received the Fokusfinder award 2011 by the Innovationsstiftung Schleswig-Holstein (ISH), the Basler AG and Philips Medical Systems.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In medical image analysis, major areas such as radiotherapy, surgery planning, and quantitative diagnostics benefit from shape modeling to facilitate solutions to analysis, segmentation and reconstruction problems. Heike Hufnagel proposes a mathematically sound statistical shape model using correspondence probabilities instead of 1-to-1 correspondences. The explicit probabilistic model is employed as shape prior in an implicit level set segmentation. Due to the particular attributes of the new model, the challenging integration of explicit and implicit representations can be done in an elegant mathematical formulation, thus combining the advantages of both explicit model and implicit segmentation. Evaluations are performed to depict the characteristics and strengths of the new model and segmentation method.The dissertation has received the Fokusfinder award 2011 by the Innovationsstiftung Schleswig-Holstein (ISH), the Basler AG and Philips Medical Systems. 172 pp. Englisch. Bestandsnummer des Verkäufers 9783834817228
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Heike Hufnagel works as a research scientist at the Institute of Medical Informatics, University of Luebeck, Germany. She holds a PhD in natural sciences.Heike Hufnagel develops a mathematically sound statistical shape model. Due to the particular attri. Bestandsnummer des Verkäufers 5379693
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In medical image analysis, major areas such as radiotherapy, surgery planning, and quantitative diagnostics benefit from shape modeling to facilitate solutions to analysis, segmentation and reconstruction problems.Heike Hufnagel proposes a mathematically sound statistical shape model using correspondence probabilities instead of 1-to-1 correspondences. The explicit probabilistic model is employed as shape prior in an implicit level set segmentation. Due to the particular attributes of the new model, the challenging integration of explicit and implicit representations can be done in an elegant mathematical formulation, thus combining the advantages of both explicit model and implicit segmentation. Evaluations are performed to depict the characteristics and strengths of the new model and segmentation method.The dissertation has received the Fokusfinder award 2011 by the Innovationsstiftung Schleswig-Holstein (ISH), the Basler AG and Philips Medical Systems.Vieweg+Teubner Verlag, Abraham-Lincoln-Straße 46, 65189 Wiesbaden 172 pp. Englisch. Bestandsnummer des Verkäufers 9783834817228
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In medical image analysis, major areas such as radiotherapy, surgery planning, and quantitative diagnostics benefit from shape modeling to facilitate solutions to analysis, segmentation and reconstruction problems. Heike Hufnagel proposes a mathematically sound statistical shape model using correspondence probabilities instead of 1-to-1 correspondences. The explicit probabilistic model is employed as shape prior in an implicit level set segmentation. Due to the particular attributes of the new model, the challenging integration of explicit and implicit representations can be done in an elegant mathematical formulation, thus combining the advantages of both explicit model and implicit segmentation. Evaluations are performed to depict the characteristics and strengths of the new model and segmentation method.The dissertation has received the Fokusfinder award 2011 by the Innovationsstiftung Schleswig-Holstein (ISH), the Basler AG and Philips Medical Systems. Bestandsnummer des Verkäufers 9783834817228
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