• DocumentCode
    1851470
  • Title

    Automatic segmentation of chromosomes in Q-band images

  • Author

    Grisan, E. ; Poletti, Enea ; Tomelleri, C. ; Ruggeri, A.

  • Author_Institution
    Univ. of Padova, Padova
  • fYear
    2007
  • fDate
    22-26 Aug. 2007
  • Firstpage
    5513
  • Lastpage
    5516
  • Abstract
    Karyotype analysis is a widespread procedure in cytogenetics to assess the possible presence of genetics defects. The procedure is lengthy and repetitive, so that an automatic analysis would greatly help the cytogeneticist routine work. Still, automatic segmentation and full disentangling of chromosomes are open issues. We propose an automatic procedure to obtain the separated chromosomes, which are then ready for a subsequent classification step. The segmentation is carried out by means of a space variant thresholding scheme, which proved to be successful even in presence of hyper- or hypo-fluorescent regions in the image. Then a greedy approach is used to identify and resolve touching and overlapping chromosomes, based on geometric evidence and image information. We show the effectiveness of the proposed method on routine data: 90% of the overlaps and 92% of the adjacencies are resolved, resulting in a correct segmentation of 96% of the chromosomes.
  • Keywords
    cellular biophysics; genetics; image segmentation; patient diagnosis; Q-band images; automatic segmentation; chromosomes; cytogenetics; genetics defects; greedy approach; karyotype analysis; space variant thresholding; Biological cells; Cancer; Cells (biology); Clustering algorithms; Fluorescence; Genetics; Image analysis; Image resolution; Image segmentation; Performance analysis; Algorithms; Artificial Intelligence; Chromosome Banding; Chromosomes, Human; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Microscopy, Fluorescence; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
  • Conference_Location
    Lyon
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-0787-3
  • Type

    conf

  • DOI
    10.1109/IEMBS.2007.4353594
  • Filename
    4353594