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: Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging
    sub title: MICCAI 2016 International Workshops, MCV and BAMBI, Athens, Greece, October 21, 2016, Revised Selected Papers
  name:
    name part: Müller, Henning.
    role:
      role term: editor.
  name:
    name part: Kelm, B. Michael.
    role:
      role term: editor.
  name:
    name part: Arbel, Tal.
    role:
      role term: editor.
  name:
    name part: Cai, Weidong.
    role:
      role term: editor.
  name:
    name part: Cardoso, M. Jorge.
    role:
      role term: editor.
  name:
    name part: Langs, Georg.
    role:
      role term: editor.
  name:
    name part: Menze, Bjoern.
    role:
      role term: editor.
  name:
    name part: Metaxas, Dimitris.
    role:
      role term: editor.
  name:
    name part: Montillo, Albert.
    role:
      role term: editor.
  name:
    name part: Wells III, William M.
    role:
      role term: editor.
  name:
    name part: Zhang, Shaoting.
    role:
      role term: editor.
  name:
    name part: Chung, Albert C.S.
    role:
      role term: editor.
  name:
    name part: Jenkinson, Mark.
    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: 2017
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIII, 222 p. 75 illus. online resource.
  abstract: This book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Medical Computer Vision, MCV 2016, and of the International Workshop on Bayesian and grAphical Models for Biomedical Imaging, BAMBI 2016, held in Athens, Greece, in October 2016, held in conjunction with the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016. The 13 papers presented in MCV workshop and the 6 papers presented in BAMBI workshop were carefully reviewed and selected from numerous submissions. The goal of the MCV workshop is to explore the use of "big data” algorithms for harvesting, organizing and learning from large-scale medical imaging data sets and for general-purpose automatic understanding of medical images. The BAMBI workshop aims to highlight the potential of using Bayesian or random field graphical models for advancing research in biomedical image analysis.
  table of contents: Constructing Subject- and Disease-Specific Effect Maps: Application to Neurodegenerative Diseases -- BigBrain: Automated Cortical Parcellation and Comparison with Existing Brain Atlases -- LATEST: Local AdapTivE and Sequential Training for Tissue Segmentation of Isointense Infant Brain MR Images -- Landmark-based Alzheimer's Disease Diagnosis Using Longitudinal Structural MR Images -- Inferring Disease Status by non-Parametric Probabilistic Embedding -- A Lung Graph-Model for Pulmonary Hypertension and Pulmonary Embolism Detection on DECT Images -- Explaining Radiological Emphysema Subtypes with Unsupervised Texture Prototypes: MESA COPD Study -- Automatic Segmentation of Abdominal MRI Using Selective Sampling and Random Walker -- Gaze2Segment: A Pilot Study for Integrating Eye-Tracking Technology into Medical Image Segmentation -- Automatic Detection of Histological Artifacts in Mouse Brain Slice Images -- Lung Nodule Classification by Jointly Using Visual Descriptors and Deep Features -- Representation Learning for Cross-Modality Classification -- Guideline-based Machine Learning for Standard Plane Extraction in 3D Cardiac Ultrasound -- A Statistical Model for Simultaneous Template Estimation, Bias Correction, and Registration of 3D Brain Images -- Bayesian Multiview Manifold Learning Applied to Hippocampus Shape and Clinical Score Data -- Rigid Slice-To-Volume Medical Image Registration through Markov Random Fields -- Sparse Probabilistic Parallel Factor Analysis for the Modeling of PET and Task-fMRI data -- Non-local Graph-based Regularization for Deformable Image Registration -- Unsupervised Framework for Consistent Longitudinal MS Lesion Segmentation. .
  note: edited by Henning Müller, B. Michael Kelm, Tal Arbel, Weidong Cai, M. Jorge Cardoso, Georg Langs, Bjoern Menze, Dimitris Metaxas, Albert Montillo, William M. Wells III, Shaoting Zhang, Albert C.S. Chung, Mark Jenkinson, Annemie Ribbens.
  subject:
    topic: Computer science
  subject:
    topic: Health informatics
  subject:
    topic: Mathematical statistics
  subject:
    topic: Computer science
    topic: Mathematics
  subject:
    topic: Artificial intelligence
  subject:
    topic: Image processing
  subject:
    topic: Pattern recognition
  subject:
    topic: Computer Science
  subject:
    topic: Image Processing and Computer Vision
  subject:
    topic: Health Informatics
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Probability and Statistics in Computer Science
  subject:
    topic: Math Applications in Computer Science
  subject:
    topic: Pattern Recognition
  classification: TA1637-1638
  classification: TA1634
  classification: 006.6
  classification: 006.37
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Lecture Notes in Computer Science, 10081
  identifier: 9783319611884
  identifier: http://dx.doi.org/10.1007/978-3-319-61188-4
  record info:
    record creation date: 170630
    record change date: 20170630102101.0
    record identifier: 978-3-319-61188-4