國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Deformable meshes for medical image ...

Kainmueller, Dagmar.

Deformable meshes for medical image segmentationaccurate automatic segmentation of anatomical structures /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Deformable meshes for medical image segmentationby Dagmar Kainmueller.
其他題名:	accurate automatic segmentation of anatomical structures /
作者:	Kainmueller, Dagmar.
出版者:	Wiesbaden :Springer Fachmedien Wiesbaden :2015.
面頁冊數:	xviii, 180 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
標題:	Image segmentation.
電子資源:	http://dx.doi.org/10.1007/978-3-658-07015-1
ISBN:	9783658070151 (electronic bk.)

Deformable meshes for medical image segmentationaccurate automatic segmentation of anatomical structures /
Kainmueller, Dagmar.

Deformable meshes for medical image segmentationaccurate automatic segmentation of anatomical structures /[electronic resource] :by Dagmar Kainmueller. - Wiesbaden :Springer Fachmedien Wiesbaden :2015. - xviii, 180 p. :ill. (some col.), digital ;24 cm. - Aktuelle Forschung Medizintechnik. - Aktuelle Forschung Medizintechnik..

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 (electronic bk.)

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

710586
Image segmentation.

LC Class. No.: TA1638.4

Dewey Class. No.: 006.6

Deformable meshes for medical image segmentationaccurate automatic segmentation of anatomical structures /
LDR:02776nmm a2200325 a 4500 001 459683
003 DE-He213
005 20150519113735.0
006 m d
007 cr nn 008maaau
008 151110s2015 gw s 0 eng d
020 $a 9783658070151 (electronic bk.)
020 $a 9783658070144 (paper)
024 7 $a 10.1007/978-3-658-07015-1 $2 doi
035 $a 978-3-658-07015-1
040 $a GP $c GP
041 0 $a eng
050 4 $a TA1638.4
072 7 $a UYQV $2 bicssc
072 7 $a COM016000 $2 bisacsh
082 0 4 $a 006.6 $2 23
090 $a TA1638.4 $b .K13 2015
100 1 $a Kainmueller, Dagmar. $3 710585
245 1 0 $a Deformable meshes for medical image segmentation $h [electronic resource] : $b accurate automatic segmentation of anatomical structures / $c by Dagmar Kainmueller.
260 $a Wiesbaden : $b Springer Fachmedien Wiesbaden : $b Imprint: Springer Vieweg, $c 2015.
300 $a xviii, 180 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Aktuelle Forschung Medizintechnik
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 Image segmentation. $3 710586
650 0 $a Diagnostic imaging $x Digital techniques. $3 191915
650 0 $a Computer vision. $3 200113
650 1 4 $a Computer Science. $3 212513
650 2 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 274492
650 2 4 $a Biomedical Engineering. $3 190464
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Aktuelle Forschung Medizintechnik. $3 675053
856 4 0 $u http://dx.doi.org/10.1007/978-3-658-07015-1
950 $a Medicine (Springer-11650)