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: Cellular Image Classification
  name:
    name part: Xu, Xiang.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Wu, Xingkun.
    role:
      role term: author.
  name:
    name part: Lin, Feng.
    role:
      role term: author.
  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: IX, 137 p. 60 illus. online resource.
  abstract: This book introduces new techniques for cellular image feature extraction, pattern recognition and classification. The authors use the antinuclear antibodies (ANAs) in patient serum as the subjects and the Indirect Immunofluorescence (IIF) technique as the imaging protocol to illustrate the applications of the described methods. Throughout the book, the authors provide evaluations for the proposed methods on two publicly available human epithelial (HEp-2) cell datasets: ICPR2012 dataset from the ICPR'12 HEp-2 cell classification contest and ICIP2013 training dataset from the ICIP'13 Competition on cells classification by fluorescent image analysis. First, the reading of imaging results is significantly influenced by one’s qualification and reading systems, causing high intra- and inter-laboratory variance. The authors present a low-order LP21 fiber mode for optical single cell manipulation and imaging staining patterns of HEp-2 cells. A focused four-lobed mode distribution is stable and effective in optical tweezer applications, including selective cell pick-up, pairing, grouping or separation, as well as rotation of cell dimers and clusters. Both translational dragging force and rotational torque in the experiments are in good accordance with the theoretical model. With a simple all-fiber configuration, and low peak irradiation to targeted cells, instrumentation of this optical chuck technology will provide a powerful tool in the ANA-IIF laboratories. Chapters focus on the optical, mechanical and computing systems for the clinical trials. Computer programs for GUI and control of the optical tweezers are also discussed. to more discriminative local distance vector by searching for local neighbors of the local feature in the class-specific manifolds. Encoding and pooling the local distance vectors leads to salient image representation. Combined with the traditional coding methods, this method achieves higher classification accuracy. Then, a rotation invariant textura…
  table of contents: Introduction -- Fundamentals -- Optical Systems for Cellular Imaging -- Image Representation with Bag-of-Words -- Image Coding -- Encoding Image Features -- Defining Feature Space for Image Classification -- Conclusions and Perspectives.
  note: by Xiang Xu, Xingkun Wu, Feng Lin.
  subject:
    topic: Engineering
  subject:
    topic: Pattern recognition
  subject:
    topic: Biomathematics
  subject:
    topic: Engineering
  subject:
    topic: Signal, Image and Speech Processing
  subject:
    topic: Pattern Recognition
  subject:
    topic: Physiological, Cellular and Medical Topics
  classification: TK5102.9
  classification: TA1637-1638
  classification: TK7882.S65
  classification: 621.382
  related item:
    title info:
      title: Springer eBooks
  identifier: 9783319476292
  identifier: http://dx.doi.org/10.1007/978-3-319-47629-2
  record info:
    record creation date: 161118
    record change date: 20161118120407.0
    record identifier: 978-3-319-47629-2