000			01707nam a2200193za04500
999			_c14367 _d14367
001			17744
008			050703s2011 gw eng d
020			_a9783834886002 99783834886002
082			_a610.28 _b223
100			_aHufnagel, Heike. _eauthor. _936246
245			_aA Probabilistic Framework for Point-Based Shape Modeling in Medical Image Analysis: _h[Electronic resource] / _cby Heike Hufnagel.
300			_aXXIII, 147 p.: _b53 illus. online resource.
520			_aIn 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.
650		0	_aENGINEERING _996
650			_933509 _aBIOCHEMICAL ENGINEERING.
710			_aSpringerLink (Online service) _9111
856			_uhttp://springer.escuelaing.metaproxy.org/book/10.1007/978-3-8348-8600-2 _yir a documento _qURL
942			_2ddc _cCF