Actions for A Probabilistic Framework for Point-Based Shape Modeling in Medical Image Analysis [electronic resource]

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A Probabilistic Framework for Point-Based Shape Modeling in Medical Image Analysis [electronic resource] / by Heike Hufnagel

Author
Hufnagel, Heike
Published
Wiesbaden : Vieweg+Teubner Verlag, 2011.
Physical Description
XXIII, 147 pages 53 illustrations : digital
Additional Creators
SpringerLink (Online service)
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Summary
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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ISBN
9783834886002
Note
AVAILABLE ONLINE TO AUTHORIZED PSU USERS.
Part Of
Springer eBooks
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