A Probabilistic Framework for Point-Based Shape Modeling in Medical Image Analysis: Aktuelle Forschung Medizintechnik – Latest Research in Medical Engineering
Autor Heike Hufnagelen Limba Engleză Paperback – 19 sep 2011
Din seria Aktuelle Forschung Medizintechnik – Latest Research in Medical Engineering
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Specificații
ISBN-13: 9783834817228
ISBN-10: 3834817228
Pagini: 172
Ilustrații: XXIII, 147 p. 53 illus.
Dimensiuni: 148 x 210 x 9 mm
Greutate: 0.25 kg
Ediția:2011
Editura: Vieweg+Teubner Verlag
Colecția Vieweg+Teubner Verlag
Seria Aktuelle Forschung Medizintechnik – Latest Research in Medical Engineering
Locul publicării:Wiesbaden, Germany
ISBN-10: 3834817228
Pagini: 172
Ilustrații: XXIII, 147 p. 53 illus.
Dimensiuni: 148 x 210 x 9 mm
Greutate: 0.25 kg
Ediția:2011
Editura: Vieweg+Teubner Verlag
Colecția Vieweg+Teubner Verlag
Seria Aktuelle Forschung Medizintechnik – Latest Research in Medical Engineering
Locul publicării:Wiesbaden, Germany
Public țintă
ResearchNotă biografică
Heike Hufnagel works as a research scientist at the Institute of Medical Informatics, University of Luebeck, Germany. She holds a PhD in natural sciences.
Textul de pe ultima copertă
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.
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.