000			02273nam a22003975i 4500
001			978-3-8348-8600-2
003			DE-He213
005			20140220083819.0
007			cr nn 008mamaa
008			111122s2011 gw | s |||| 0|eng d
020			_a9783834886002 _9978-3-8348-8600-2
024	7		_a10.1007/978-3-8348-8600-2 _2doi
050		4	_aR856-857
072		7	_aMQW _2bicssc
072		7	_aTEC009000 _2bisacsh
082	0	4	_a610.28 _223
100	1		_aHufnagel, Heike. _eauthor.
245	1	2	_aA Probabilistic Framework for Point-Based Shape Modeling in Medical Image Analysis _h[electronic resource] / _cby Heike Hufnagel.
264		1	_aWiesbaden : _bVieweg+Teubner Verlag, _c2011.
300			_aXXIII, 147p. 53 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
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.
650		0	_aBiomedical engineering.
650	1	4	_aEngineering.
650	2	4	_aBiomedical Engineering.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783834817228
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-8348-8600-2
912			_aZDB-2-ENG
999			_c108735 _d108735