國立虎尾科技大學 |

Deformable Meshes for Medical Image Segmentation = Accurate Automatic Segmentation of Anatomical Structures /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Deformable Meshes for Medical Image Segmentation/ by Dagmar Kainmueller.
其他題名:	Accurate Automatic Segmentation of Anatomical Structures /
作者:	Kainmueller, Dagmar.
面頁冊數:	XVIII, 180 p. 52 illus., 30 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Optical data processing. -
電子資源:	https://doi.org/10.1007/978-3-658-07015-1
ISBN:	9783658070151

Deformable Meshes for Medical Image Segmentation = Accurate Automatic Segmentation of Anatomical Structures /
Kainmueller, Dagmar.

Deformable Meshes for Medical Image SegmentationAccurate Automatic Segmentation of Anatomical Structures /[electronic resource] :by Dagmar Kainmueller. - 1st ed. 2015. - XVIII, 180 p. 52 illus., 30 illus. in color.online resource. - Aktuelle Forschung Medizintechnik – Latest Research in Medical Engineering,2625-9354. - Aktuelle Forschung Medizintechnik – Latest Research in Medical Engineering,.

Deformable Meshes for Accurate Automatic Segmentation -- Omnidirectional Displacements for Deformable Surfaces (ODDS) -- Coupled Deformable Surfaces for Multi-object Segmentation.

Segmentation of anatomical structures in medical image data is an essential task in clinical practice. Dagmar Kainmueller introduces methods for accurate fully automatic segmentation of anatomical structures in 3D medical image data. The author’s core methodological contribution is a novel deformation model that overcomes limitations of state-of-the-art Deformable Surface approaches, hence allowing for accurate segmentation of tip- and ridge-shaped features of anatomical structures. As for practical contributions, she proposes application-specific segmentation pipelines for a range of anatomical structures, together with thorough evaluations of segmentation accuracy on clinical image data. As compared to related work, these fully automatic pipelines allow for highly accurate segmentation of benchmark image data. Contents Deformable Meshes for Accurate Automatic Segmentation Omnidirectional Displacements for Deformable Surfaces (ODDS) Coupled Deformable Surfaces for Multi-object Segmentation From Surface Mesh Deformations to Volume Deformations Segmentation of Anatomical Structures in Medical Image Data Target Groups Academics and practitioners in the fields of computer science, medical imaging, and automatic segmentation. The Author Dagmar Kainmueller works as a research scientist at the Max Planck Institute of Molecular Cell Biology and Genetics in Dresden, Germany, with a focus on bio image analysis. The Editor The series Aktuelle Forschung Medizintechnik – Latest Research in Medical Engineering is edited by Thorsten M. Buzug. .

ISBN: 9783658070151

Standard No.: 10.1007/978-3-658-07015-1doiSubjects--Topical Terms:

639187
Optical data processing.

LC Class. No.: TA1630-1650

Dewey Class. No.: 006.6

Deformable Meshes for Medical Image Segmentation = Accurate Automatic Segmentation of Anatomical Structures /
LDR:03205nam a22003975i 4500 001 962641
003 DE-He213
005 20200701094142.0
007 cr nn 008mamaa
008 201211s2015 gw | s |||| 0|eng d
020 $a 9783658070151 $9 978-3-658-07015-1
024 7 $a 10.1007/978-3-658-07015-1 $2 doi
035 $a 978-3-658-07015-1
050 4 $a TA1630-1650
072 7 $a UYQV $2 bicssc
072 7 $a COM016000 $2 bisacsh
072 7 $a UYQV $2 thema
082 0 4 $a 006.6 $2 23
100 1 $a Kainmueller, Dagmar. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1062551
245 1 0 $a Deformable Meshes for Medical Image Segmentation $h [electronic resource] : $b Accurate Automatic Segmentation of Anatomical Structures / $c by Dagmar Kainmueller.
250 $a 1st ed. 2015.
264 1 $a Wiesbaden : $b Springer Fachmedien Wiesbaden : $b Imprint: Springer Vieweg, $c 2015.
300 $a XVIII, 180 p. 52 illus., 30 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Aktuelle Forschung Medizintechnik – Latest Research in Medical Engineering, $x 2625-9354
505 0 $a Deformable Meshes for Accurate Automatic Segmentation -- Omnidirectional Displacements for Deformable Surfaces (ODDS) -- Coupled Deformable Surfaces for Multi-object Segmentation.
520 $a Segmentation of anatomical structures in medical image data is an essential task in clinical practice. Dagmar Kainmueller introduces methods for accurate fully automatic segmentation of anatomical structures in 3D medical image data. The author’s core methodological contribution is a novel deformation model that overcomes limitations of state-of-the-art Deformable Surface approaches, hence allowing for accurate segmentation of tip- and ridge-shaped features of anatomical structures. As for practical contributions, she proposes application-specific segmentation pipelines for a range of anatomical structures, together with thorough evaluations of segmentation accuracy on clinical image data. As compared to related work, these fully automatic pipelines allow for highly accurate segmentation of benchmark image data. Contents Deformable Meshes for Accurate Automatic Segmentation Omnidirectional Displacements for Deformable Surfaces (ODDS) Coupled Deformable Surfaces for Multi-object Segmentation From Surface Mesh Deformations to Volume Deformations Segmentation of Anatomical Structures in Medical Image Data Target Groups Academics and practitioners in the fields of computer science, medical imaging, and automatic segmentation. The Author Dagmar Kainmueller works as a research scientist at the Max Planck Institute of Molecular Cell Biology and Genetics in Dresden, Germany, with a focus on bio image analysis. The Editor The series Aktuelle Forschung Medizintechnik – Latest Research in Medical Engineering is edited by Thorsten M. Buzug. .
650 0 $a Optical data processing. $3 639187
650 0 $a Biomedical engineering. $3 588770
650 1 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 671334
650 2 4 $a Biomedical Engineering and Bioengineering. $3 1211019
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783658070168
776 0 8 $i Printed edition: $z 9783658070144
830 0 $a Aktuelle Forschung Medizintechnik – Latest Research in Medical Engineering, $x 2625-9354 $3 1254465
856 4 0 $u https://doi.org/10.1007/978-3-658-07015-1
912 $a ZDB-2-SME
912 $a ZDB-2-SXM
950 $a Medicine (SpringerNature-11650)
950 $a Medicine (R0) (SpringerNature-43714)