• DocumentCode
    1316203
  • Title

    Geometric separation of partially overlapping nonrigid objects applied to automatic chromosome classification

  • Author

    Agam, Gady ; Dinstein, Itshak

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Ben-Gurion Univ. of the Negev, Beer-Sheva, Israel
  • Volume
    19
  • Issue
    11
  • fYear
    1997
  • fDate
    11/1/1997 12:00:00 AM
  • Firstpage
    1212
  • Lastpage
    1222
  • Abstract
    A common task in cytogenetic tests is the classification of human chromosomes. Successful separation between touching and overlapping chromosomes in a metaphase image is vital for correct classification. Current systems for automatic chromosome classification are mostly interactive and require human intervention for correct separation between touching and overlapping chromosomes. Since chromosomes are nonrigid objects, special separation methods are required to segregate them. Common methods for overlapping chromosomes separation between touching chromosomes tend to fail where ambiguity or incomplete information are involved, and so are unable to segregate overlapping chromosomes. The proposed approach treats the separation problem as an identification problem, and, in this way, manages to segregate overlapping chromosomes. This approach encompasses low-level knowledge about the objects and uses only extracted information, therefore, it is fast and does not depend on the existence of a separating path. The method described in this paper can be adopted for other applications, where separation between touching and overlapping nonrigid objects is required
  • Keywords
    biological techniques; biology computing; cellular biophysics; computational geometry; genetics; image classification; image segmentation; optical microscopy; automatic chromosome classification; cytogenetic tests; geometric separation; identification; image segregation; metaphase image; partially overlapping nonrigid objects; touching objects; Arm; Automatic testing; Biological cells; Computational geometry; Data mining; Humans; Image analysis; Image recognition; Image segmentation; Prototypes;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.632981
  • Filename
    632981