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: Bayesian and grAphical Models for Biomedical Imaging
    sub title: First International Workshop, BAMBI 2014, Cambridge, MA, USA, September 18, 2014, Revised Selected Papers
  name:
    name part: Cardoso, M. Jorge.
    role:
      role term: editor.
  name:
    name part: Simpson, Ivor.
    role:
      role term: editor.
  name:
    name part: Arbel, Tal.
    role:
      role term: editor.
  name:
    name part: Precup, Doina.
    role:
      role term: editor.
  name:
    name part: Ribbens, Annemie.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2014
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: X, 131 p. 54 illus. online resource.
  abstract: This book constitutes the refereed proceedings of the First International Workshop on Bayesian and grAphical Models for Biomedical Imaging, BAMBI 2014, held in Cambridge, MA, USA, in September 2014 as a satellite event of the 17th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2014. The 11 revised full papers presented were carefully reviewed and selected from numerous submissions with a key aspect on probabilistic modeling applied to medical image analysis. The objectives of this workshop compared to other workshops, e.g. machine learning in medical imaging, have a stronger mathematical focus on the foundations of probabilistic modeling and inference. The papers highlight the potential of using Bayesian or random field graphical models for advancing scientific research in biomedical image analysis or for the advancement of modeling and analysis of medical imaging data.
  note: edited by M. Jorge Cardoso, Ivor Simpson, Tal Arbel, Doina Precup, Annemie Ribbens.
  subject:
    topic: Computer science
  subject:
    topic: Algorithms
  subject:
    topic: Computer science
    topic: Mathematics
  subject:
    topic: Artificial intelligence
  subject:
    topic: Computer graphics
  subject:
    topic: Image processing
  subject:
    topic: Pattern recognition
  subject:
    topic: Computer Science
  subject:
    topic: Algorithm Analysis and Problem Complexity
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Image Processing and Computer Vision
  subject:
    topic: Pattern Recognition
  subject:
    topic: Computer Graphics
  subject:
    topic: Discrete Mathematics in Computer Science
  classification: QA76.9.A43
  classification: 005.1
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Lecture Notes in Computer Science, 8677
  identifier: 9783319122892
  identifier: http://dx.doi.org/10.1007/978-3-319-12289-2
  record info:
    record creation date: 140922
    record change date: 20151204175222.0
    record identifier: 978-3-319-12289-2