Deformable meshes for medical image segmentation : accurate automatic segmentation of anatomical structures /

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Bibliographic Details
Author / Creator:Kainmueller, Dagmar, author.
Imprint:Wiesbaden : Springer Vieweg, [2014]
Description:1 online resource (xviii, 180 pages) : illustrations (some color).
Series:Aktuelle Forschung Medizintechnik
Aktuelle Forschung Medizintechnik.
Subject:Image segmentation.
Diagnostic imaging -- Digital techniques.
Computer vision.
Computer Science.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Biomedical Engineering.
COMPUTERS -- General.
Computer vision.
Diagnostic imaging -- Digital techniques.
Image segmentation.
Electronic books.
Format: E-Resource Book
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Hidden Bibliographic Details
Notes:"Dissertation University of Lübeck, 2013."
Includes bibliographical references.
Online resource; title from PDF title page (SpringerLink, viewed Sept. 3, 2014).
Summary:? 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 anatom.
Other form:Print version: Kainmueller, Dagmar. Deformable Meshes for Medical Image Segmentation : Accurate Automatic Segmentation of Anatomical Structures. Dordrecht : Springer, ©2014 9783658070144
Standard no.:10.1007/978-3-658-07015-1