rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Deformable Meshes for Medical Image Segmentation
    sub title: Accurate Automatic Segmentation of Anatomical Structures
  name:
    name part: Kainmueller, Dagmar.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2015
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XVIII, 180 p. 52 illus., 30 illus. in color. online resource.
  abstract: 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. .
  table of contents: Deformable Meshes for Accurate Automatic Segmentation -- Omnidirectional Displacements for Deformable Surfaces (ODDS) -- Coupled Deformable Surfaces for Multi-object Segmentation.
  note: by Dagmar Kainmueller.
  subject:
    topic: Computer science
  subject:
    topic: Computer graphics
  subject:
    topic: Biomedical engineering
  subject:
    topic: Computer Science
  subject:
    topic: Computer Imaging, Vision, Pattern Recognition and Graphics
  subject:
    topic: Biomedical Engineering
  classification: T385
  classification: TA1637-1638
  classification: TK7882.P3
  classification: 006.6
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Aktuelle Forschung Medizintechnik – Latest Research in Medical Engineering
  identifier: 9783658070151
  identifier: http://dx.doi.org/10.1007/978-3-658-07015-1
  record info:
    record creation date: 140818
    record change date: 20151204173000.0
    record identifier: 978-3-658-07015-1